DETAILED ACTION
Status of the Application
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 4, 2026, has been entered.
In response, the Applicant amended claims 1, 8, and 15. Claim 20 was cancelled. Claim 21 was added. Claims 1-19 and 21 are pending and currently under consideration for patentability.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendments and Arguments
v Applicant’s arguments, with respect to the rejection of claims 1-19 and 21 under 35 U.S.C. 101 have been fully considered and are not persuasive. The rejections of claims 1-19 and 21 under 35 U.S.C. 101 have been maintained accordingly.
Applicant specifically argues that
1) “integrated the alleged abstract idea into a practical application because the claims are directed to an unconventional technical solution to the technical problem in the field of online social media platform site…the present application describes technical problems that exists in the field
with online social media platforms. Applicant notes that detecting an issue or a topic
discussed on a social media platform that is increasing in visibility or awareness has a
speed or timeliness component to the problem that did not exist before the rise of the
Internet…the unconventional technical solution recited in the claims involves using
various limitations for addressing the technical problems for generating time-sensitive
notifications associated with online social media platforms…training a machine learning model…preprocessing data…limitations relating to timely-sensitive notifications that are controlled when they are displayed and removed from another computing device (e.g., client device)…establishing a connection using the alert and transmitting additional information related to the alert…a specific implementation that is unconventional in the field for the technical problem providing time-sensitive notifications related to "an issue or a topic discussed on the social media platform 203 [that] is increasing in visibility or awareness (e.g., "going viral")."
Examiner respectfully disagrees with Applicant’s first argument.
The alleged problem that a subject of a topic/sentiment may not become aware of public awareness/discourse/sentiment associated with the topic due to the speed at which information/sentiment is spread on social media problems is not a technical problem. This is a subjective problem from the perspective of the subject (e.g., because it depends on whether or not a subject is interested in the public opinions/sentiments to begin with). This is fundamentally different than, for example, the transmission of stock quote data at issue in Example 21 in the USPTO’s 2014 Interim Guidance on Subject Matter Eligibility (2014 IEG). Example 21 related to a technical problem associated with an inability for subscribers to receive desired alerts because their computers were offline (not connected to the internet) at a time of an alert. The alleged problem addressed by the instant invention is non-analogous to this problem.
Furthermore, Examiner notes Applicant’s claimed invention does not necessarily reflect a solution to this problem. For example, the claims merely involve a predefined interval of time for obtaining submitted content, determining a negative sentiment score for the interval of time, determining the negative sentiment score exceeds a first moving average sentiment score, and generating an alert accordingly. There is nothing to say that the time intervals involved are large. In other words, it is not apparent that the claims are conserved with time-sensitivity or address issues associated with speed or timeliness.
Furthermore, the alleged solution does not involve an unconventional arrangement of additional elements that solve this problem associated with sentiment volume/velocity. The claimed solution to the speed at which information/sentiment is spread on social media is simply to use one or more general purpose computers to analyze the shared messages rather than a human (e.g., because computers can process more information than a human can and because they can process the information more quickly than humans can). The combination of “a computing device comprising a processor and memory” and “machine learning model” is not only a conventional arrangement of additional elements, but it amounts to a requirement to apply the recited abstract idea using a general-purpose computer. Again, the solution in Example 21 is quite different. The solution involved providing a stock viewer application to subscribers to install on their remote individual computers, and the claimed invention involved interactions between a transmission server, a separate wireless device associated with the subscriber, the provided stock viewer application, and a remote subscriber computer.
Similarly, that the generated alert is formatted “to fit within a data allotment based at least in part on the data allotment being associated with a specific messaging of a recipient” and/or displayed on “a client device” and/or “activates a client application executing on the client device to cause the client application to display the alert” and further “connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device” serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, it/they serve(s) to limit the application of the abstract idea to computing environments, such as distributed computing environments and/or the internet, where information is represented digitally, exchanged between computers over a network, and presented using graphical user interfaces, and more specifically to computing environments where a web portal or web application is used to display digital information. Applicant’s own disclosure explains that the alert could be provided via a variety of desired formats (e.g., email, text message, etc. – see [0049]-[0051] of the as-filed specification). The formatting requirement serves merely to limit the alert transmission to a certain type of message (e.g., SMS text message), The requirement to send an alert that activates a client application and enable the client device to connect to the computing device across a network to view additional information about the alert (i.e., that the alert is sent to a web application), is merely a particular technological environment or field of use used for alerting an individual. The same is true for the “connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device” limitation, which merely requires displaying additional information via the web app. Use of a web application to display an alert is not only a simply matter of design choice (e.g., by the Applicant and/or by the interested party), it is non-inventive (e.g., as demonstrated at least by the lack of technical detail provided in Applicant’s disclosure). This reasoning was demonstrated in Intellectual Ventures I LLC v. Capital One Bank (Fed. Cir. 2015), where the court determined "an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer"). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(g)).
Applicant specifically argues that
2) “the claims include multiple additional elements that amount to significantly more than the alleged abstract idea of a "certain methods of organizing human activity," as alleged in the Office Action on page …these additional elements are integrated into an inventive concept for a time-sensitive notification system for detecting an issue or a topic discussed on the social media platform 203 is increasing in visibility or awareness on an online social media platform because these additional elements contributed detecting in a timely manner issues or topics that are increasing in visibility on online social media platforms and controlling the display of the notification on a client device..”
Examiner respectfully disagrees with Applicant’s second argument.
As discussed above with respect to the first argument, these “additional” elements, when considered alone and/or in combination with one another, amounts to a requirement to apply the recited abstract idea using a general-purpose computer and serves merely to generally link the use of the judicial exception to a particular technological environment or field of use.
v Applicant’s arguments, with respect to the rejection of amended claims 1, 8, and 15 (as well as each of the dependent claims) under 35 U.S.C. §103 have been considered, but are not persuasive. Applicant argues Vick doesn’t disclose “connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device”. Examiner respectfully disagrees. Applicant appears to be arguing for a narrower interpretation of “based at least in part on the alert being received by the client device” and “associated with the alert” than what is required from the claim language, as these are broad conditions. Vick discloses a web app or other mobile app may provide the interfaces discussed throughout the disclosure ([0083]). As such, the alert (e.g., per [0084]) is presented via one or more user interfaces via this software app. Opening the app via the user device is necessary to display the device. Vick further discloses other functionality that the user may engage with via the app while it is open, such as viewing historic a previous negative sentiment score from a previous period of time ([0043] “s, a user may select a timeframe for relevant posts relating to a topic to be scored. This may allow a user to retrieve a historic score for a period of time of interest”, [0065] “the page sent from the server may include a previously determined score.”, [0100] “real-time graphing 1910 that provides a visual display of the social influence of a given asset or topic. Such an interface may also include a navigation control 1920 configured to allow a user to navigate back in time to see social influence data on a specific asset or topic from past time periods (e.g., weeks, months, or years ago).”). Other information may be dynamically displayed via the app’s interface(s) when it is open ([0042]-[0045] “The score may be periodically (e.g., every determined number of seconds, minutes, hours, days, etc.) logged to allow asset score changes to be observed over time…embodiments may derive further scoring data, such as the change in an asset's score over a period of time, high and low scores and their associated times, inflection points in the rate of change of a score, trending information, and the like. Embodiments may also flag specific social media posts that go viral, thus correlating to significant events relating to an asset's score or posters that have a significant effect on an asset's score. As will be discussed below, graphical models may be generated to provide user interface displays of scores and derived scoring data”, [0056] “The server may then send the score to the client and the score may be displayed in the page for viewing by a user. This constant flow may only add a few milliseconds of delay to loading a page while allowing users to receive live scores for a requested assets and social media content aggregated and normalized from plural networks.”, [0075] “FIG. 12 also includes user interface controls 930 to allow a user to browse historic posts (e.g., new posts may appear from the left”). In both instances, the client application of the client device (that is open, as is required to display the received alert – therefor based at least in part on the alert being received by the client device) is connecting across the network with the server to receive additional information associated with the alert (e.g., historic data, historic scores, associated post data, related trends/metrics associated in some with the alert). Examiner notes Bailey also discloses this limitation.
Applicant further argues Vick fails to disclose “the subset of posts being returned from the machine learning model in a data structure…determining a negative sentiment score…based at least in part on receiving the data structure of the subset of posts”. Examiner respectfully disagrees. Applicant again appears to be relying on an overly narrow interpretation of “the subset of posts…in a data structure”. Any returned subset of posts, any information associated with the returned subset of posts, and any score returned from the machine learning model, is necessarily “in a data structure” (i.e., it is structured data/information within the computer) to enable the server and web/mobile apps to display this information. It is also stored in a database on the server ([0038], [0066]), meaning it is structured. Examiner notes Bailey also discloses this limitation.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
v Claim(s) 1-19 and 21 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1:
Claim(s) 8-14 is/are drawn to methods (i.e., a process), claim(s) 1-7 is/are drawn to systems (i.e., a machine/manufacture), and claim(s) 15-19 and 21 is/are drawn to non-transitory media (i.e., a machine/manufacture). As such, claims 1-19 and 21 is/are drawn to one of the statutory categories of invention (Step 1: YES).
Step 2A - Prong One:
In prong one of step 2A, the claim(s) is/are analyzed to evaluate whether it/they recite(s) a judicial exception.
Claim 1 (representative of independent claim(s) 8 and 15) recites/describes the following steps;
train a…model for sentiment analysis of a plurality of social media posts based at least in part on applying a…algorithm to a training data set that comprises a sample text in a format of a respective social media platform, the…model being trained to classify a respective social media post as at least one of positive, negative, or neutral;
identify an expiration of a predefined interval of time for obtaining user submitted content from a social media platform site
preprocess the user submitted content by removing a media file from a plurality of user posts to generate a plurality of modified user posts in a plaintext format;
identify a subset of posts with a negative sentiment…the subset of posts being returned…in a data structure
determine a negative sentiment score of the subset of posts with the negative sentiment for the interval of time based at least in part on receiving the data structure of the subset of posts;
determine the negative sentiment score exceeds a first moving average sentiment score;
generate an alert in response to the determination that the negative sentiment score exceeds the first moving average sentiment score;
format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging of a recipient;
transmit the alert…based at least in part on the alert being formatted
transmit additional information associated with the alert based at least in part on the alert being received
halt the alert based at least in part on a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score
These steps, under its broadest reasonable interpretation, describe or set-forth a business process for determining whether user-generated posts having negative sentiment are trending or going viral and alerting relevant entities (e.g., businesses, advertisers, etc., so that they may be made aware of a reputational crisis) accordingly, which amounts to a commercial or legal interactions (specifically, an advertising, marketing or sales activity or behavior; business relations). These limitations therefore fall within the “certain methods of organizing human activity” subject matter grouping of abstract ideas.
Additionally, and/or alternatively, each of the above-recited steps/functions, under their broadest reasonable interpretation, encompass a human manually (e.g., in their mind, or using paper and pen) performing one or more concepts performed in the human mind, such as one or more observations, evaluations, judgments, opinions, but for the recitation of generic computer components. If one or more claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) in the mind but for the recitation of generic computer components, then it falls within the “mental processes” subject matter grouping of abstract ideas.
As such, the Examiner concludes that claim 1 recites an abstract idea (Step 2A – Prong One: YES).
Independent claim(s) 8 and 15 recite/describe nearly identical steps (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this/these claim(s) is/are therefore determined to recite an abstract idea under the same analysis.
Each of the depending claims likewise recite/describe these steps (by incorporation - and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this/these claim(s) is/are therefore determined to recite an abstract idea under the same analysis. Any element(s) recited in a dependent claim that are not specifically identified/addressed by the Examiner under step 2A (prong two) or step 2B of this analysis shall be understood to be an additional part of the abstract idea recited by that particular claim. The same reasoning is similarly applicable to the limitations in the remaining dependent claims, and their respective limitations are not reproduced here for the sake of brevity.
Step 2A - Prong Two:
In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “addition element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
The claim(s) recite the additional elements/limitations of
“a system, comprising: a computing device comprising a processor and a memory; and machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least…” (claim 1)
“computer-implemented…by at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…” (claim 8)
“A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least…” (claim 15)
“a machine learning model… a machine learning algorithm…the machine learning model being trained… based at least in part on submitting the plurality of modified user posts to the machine learning model … returned from the machine learning model” (claims 1, 8, and 15)
“transmit the alert to a client device associated with the recipient…wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert, connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device…halt the alert at the client device by instructing the client device to cease to display the alert on the client device” (claims 1, 8, and 15)
“wherein the machine-readable instructions that cause the computing device to…further causes the computing device to at least…” (claim 3)
“wherein…the machine-readable instructions that halt the alert at the client device by instructing the client device to cease to display the alert further cause the computing device to at least…” (claims 4-6)
“transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient” (claims 7 and 14)
“by the at least one computing device… by the at least one computing device” (claims 10-13)
“wherein the machine-readable instructions that cause the computing device to… further cause the computing device to at least…” (claim 17)
“wherein… the machine-readable instructions further cause the computing device to at least…” (claims 18 and 19)
“wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to…stored in a memory associated with the computing device” (claim 21)
The requirement to execute the claimed steps/functions using “a system, comprising: a computing device comprising a processor and a memory; and machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least…” (claim 1) or wherein the method is “computer-implemented…by at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…” (claim 8) or “A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least…” (claim 15) and/or the recitation of “wherein the machine-readable instructions that cause the computing device to…further causes the computing device to at least…” (claim 3) and/or “wherein…the machine-readable instructions that halt the alert at the client device by instructing the client device to cease to display the alert further cause the computing device to at least…” (claims 4-6) and/or “by the at least one computing device… by the at least one computing device” (claims 10-13) and/or “wherein the machine-readable instructions that cause the computing device to… further cause the computing device to at least…” (claim 17) and/or “wherein… the machine-readable instructions further cause the computing device to at least…” (claims 18 and 19) and/or “wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to…stored in a memory associated with the computing device” (claim 21) is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Applicant’s own disclosure explains that these “additional” elements may be embodied as a general-purpose computer (e.g., the as-filed specification at paragraphs [0013] “aggregator system 206, and/or the analysis system 209 can each include one or more computing devices that include a processor, a memory, and/or a network interface” and [0066] “the applications and systems described herein can be embodied in software or code executed by general purpose hardware as discussed above, as an alternative the same can also be embodied in dedicated hardware or a combination of software/general purpose hardware and dedicated hardware…Such technologies are generally well known by those skilled in the art and, consequently, are not described in detail herein."). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
The recitation of “train a machine learning model… a machine learning algorithm…the machine learning model being trained… based at least in part on submitting the plurality of modified user posts to the machine learning model … returned from the machine learning model” (claims 1, 8, and 15) provides nothing more than mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f) and the July 2024 Subject Matter Eligibility Examples and corresponding analysis. MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. The machine learning model is used to generally apply the abstract idea without placing any limits on how the machine learning model functions. Rather, these limitations only recite the outcome of “determine a negative sentiment score…” and do not include any details about how the “determining” is accomplished. See MPEP 2106.05(f) and the July 2024 Subject Matter Eligibility Examples and corresponding analysis. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
The recited additional element(s) of “transmit the alert to a client device associated with the recipient…wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert, connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device…halt the alert at the client device by instructing the client device to cease to display the alert on the client device” (claims 1, 8, and 15) and/or “transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient” (claims 7 and 14) and/or “wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to…stored in a memory associated with the computing device” (claim 21) serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, it/they serve(s) to limit the application of the abstract idea to computing environments, such as distributed computing environments and/or the internet, where information is represented digitally, exchanged between computers over a network, and presented using graphical user interfaces, and more specifically to computing environments where a web portal or web application is used to display digital information. Applicant’s own disclosure explains that the alert could be provided via a variety of desired formats (e.g., email, text message, etc. – see [0049]-[0051] of the as-filed specification). Requirement to send an alert that activates a client application and enable the client device to connect to the computing device across a network to view additional information about the alert (i.e., that the alert is sent to a web application), is merely a particular technological environment or field of use used for alerting an individual. Use of a web application to display an alert is not only a simply matter of design choice (e.g., by the Applicant and/or by the interested party), it is non-inventive (e.g., as demonstrated at least by the lack of technical detail provided in Applicant’s disclosure). This reasoning was demonstrated in Intellectual Ventures I LLC v. Capital One Bank (Fed. Cir. 2015), where the court determined "an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer"). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(g)).
The recitation of “train a machine learning model… a machine learning algorithm…the machine learning model being trained… based at least in part on submitting the plurality of modified user posts to the machine learning model … returned from the machine learning model” (claims 1, 8, and 15) also merely indicates a field of use or technological environment in which the judicial exception is performed. Although the additional element limits the identified judicial exceptions to use of “machine learning models”, this type of limitation merely confines the use of the abstract idea to a particular technological environment (machine learning) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h) and the July 2024 Subject Matter Eligibility Examples and corresponding analysis. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(g)).
The recited additional element(s) of “transmit the alert to a client device associated with the recipient…wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert, connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device…halt the alert at the client device by instructing the client device to cease to display the alert on the client device” (claims 1, 8, and 15) and/or “transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient” (claims 7 and 14) additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere post-solution activity in conjunction with an abstract idea). The term “extra-solution activity” is understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. The recited additional element(s) do are deemed “extra-solution” because such solution-outputting/transmission steps have long been held to be insignificant pre/post-solution activity. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(h) and (g)).
Furthermore, although the claims recite a specific sequence of computer-implemented functions, and although the specification suggests certain functions may be advantageous for various reasons (e.g., business reasons), the Examiner has determined that the ordered combination of claim elements (i.e., the claims as a whole) are not directed to an improvement to computer functionality/capabilities, an improvement to a computer-related technology or technological environment, and do not amount to a technology-based solution to a technology-based problem. For example, Applicant’s as-filed specification suggests that it is advantageous to implement the claimed business process because dong so can help entities/businesses to become aware of emerging crisis or problems with their reputation as reflected in user comments/posts (see, for example, Applicant’s as-filed disclosure at paragraphs [0001] & [0010]). These are non-technical business advantages/improvements. At most, the ordered combination of claim elements is directed to a non-technical improvement to an abstract idea itself (e.g., an improved way of detecting viral negative sentiment or alerting a business regarding negative sentiment).
Dependent claims 2, 9, and 16 fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims 2, 9, and 16 is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea recited in each respective claim). For example, claim 2 recites “wherein the first moving average sentiment score is a moving average of the negative sentiment score for a defined preceding time period.” This is an abstract limitation which further sets forth the abstract idea encompassed by claim 2. This limitation is not an “additional element”, and therefore it is not subject to further analysis under Step 2A- Prong Two or Step 2B. The same logic applies to each of the other dependent claims, whose limitations are not being repeated here for the sake of brevity and clarity. With respect to the other dependent claims not specifically listed here - each of the limitations/elements recited in these dependent claims other than those identified as being “additional” elements above, is/are further part of the abstract idea for each respective dependent claim (i.e. it should be understood that these limitations are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B:
In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, is/are sufficient to ensure that the claims amount to significantly more than the judicial exception. This analysis is also termed a search for an "inventive concept." An "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966)
As discussed above in “Step 2A – Prong 2”, the requirement to execute the claimed steps/functions using “a system, comprising: a computing device comprising a processor and a memory; and machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least…” (claim 1) or wherein the method is “computer-implemented…by at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…by the at least one computing device…” (claim 8) or “A non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least…” (claim 15) and/or the recitation of “wherein the machine-readable instructions that cause the computing device to…further causes the computing device to at least…” (claim 3) and/or “wherein…the machine-readable instructions that halt the alert at the client device by instructing the client device to cease to display the alert further cause the computing device to at least …” (claims 4-6) and/or “by the at least one computing device… by the at least one computing device” (claims 10-13) and/or “wherein the machine-readable instructions that cause the computing device to… further cause the computing device to at least…” (claim 17) and/or “wherein… the machine-readable instructions further cause the computing device to at least…” (claims 18 and 19) and/or “wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to…stored in a memory associated with the computing device” (claim 21) is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as “significantly more” (see MPEP 2106.05(f)).
As discussed above in “Step 2A – Prong 2”, the recitation of “train a machine learning model… a machine learning algorithm…the machine learning model being trained… based at least in part on submitting the plurality of modified user posts to the machine learning model … returned from the machine learning model” (claims 1, 8, and 15) is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as “significantly more” (see MPEP 2106.05(f)).
As discussed above in “Step 2A – Prong 2”, the recited additional element(s) of “transmit the alert to a client device associated with the recipient…wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert, connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device…halt the alert at the client device by instructing the client device to cease to display the alert on the client device” (claims 1, 8, and 15) and/or “transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient” (claims 7 and 14) and/or “wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to…stored in a memory associated with the computing device” (claim 21) serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not qualify as “significantly more” (see MPEP 2106.05(g)).
As discussed above in “Step 2A – Prong 2”, the recitation of “train a machine learning model… a machine learning algorithm…the machine learning model being trained… based at least in part on submitting the plurality of modified user posts to the machine learning model … returned from the machine learning model” (claims 1, 8, and 15) also serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. These limitations therefore do not qualify as “significantly more” (see MPEP 2106.05(g)).
As discussed above in “Step 2A – Prong 2”, the recited additional element(s) of “transmit the alert to a client device associated with the recipient…wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert, connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device…halt the alert at the client device by instructing the client device to cease to display the alert on the client device” (claims 1, 8, and 15) and/or “transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient” (claims 7 and 14) additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere post-solution activity in conjunction with an abstract idea). These additional element(s), taken individually or in combination, additionally amount to well-understood, routine and conventional activities previously known to the industry, specified at a high level of generality, appended to the judicial exception. These additional elements, taken individually or in combination, are well-understood, routine and conventional to those in the field of digital alerting and/or sentiment analysis alerting. These limitations therefore do not qualify as “significantly more”. (see MPEP 2106.05(d)). This conclusion is based on a factual determination. The determination that receiving data/messages over a network is well-understood, routine, and conventional is supported by Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), and MPEP 2106.05(d)(II), which note the well-understood, routine, conventional nature of receiving data/messages over a network. Furthermore, Examiner takes Official Notice that these steps were well-understood, routine, and conventional at the effective filing date of the claimed invention. Furthermore, the lack of technical detail/description in Applicant’s own specification provides implicit evidence that these steps were well-understood, routine, and conventional.
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer, generally link the abstract idea to a particular technological environment or field of use, append the abstract idea with insignificant extra solution activity associated with the implementation of the judicial exception, (e.g., mere data gathering, post-solution activity), and appended with well-understood, routine and conventional activities previously known to the industry.
Dependent claims 2, 9, and 16 fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims 2, 9, and 16 is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e. they are part of the abstract idea identified by the Examiner to which each respective claim is directed).
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-19 and 21 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
v Claim 1 recites “format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging of a recipient” and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The metes and bounds of formatting the alert based at least in part on the data allotment being associated with a specified messaging of a recipient is unclear. How would the formatting to fit within a data allotment be done differently whether based on the data allotment being associated with a specified messaging format of a recipient or whether not based on the data allotment being associated with a specified messaging format of a recipient. Claims 8 and 15 relatedly require “formatting…the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified format of a recipient”. Again, how would the formatting to fit within a data allotment be done differently whether based at least in part on the data allotment being associated with a specified format of a recipient or whether not based at least in part on the data allotment being associated with a specified format of a recipient. Either way, the alert is formatted to fit within the data allotment. Therefore, the claim is indefinite for failing to particularly and distinctly claim the subject matter which the application regards as the invention.
For the purpose of examination, each of these phrases will be interpreted as being “format the alert to fit within a data allotment associated with a specified messaging format of a recipient.”
Each of the dependent claims are similarly rejected by virtue of their dependency on one of these claims.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
v Claims 1, 2, 4-9, 11-16, 18, 19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Vick et al. (U.S. PG Pub No. 2013/0124653, May 16, 2013 – hereinafter “Vick”) in view of Bala (U.S. PG Pub No. 2022/0292527, September 15, 2022 – hereinafter “Bala”) and further in view of Bailey et al. (U.S. PG Pub No. 2010/0312769 December 9, 2010 – hereinafter “Bailey”)
With respect to claims 1, 8, and 15, Vick teaches a system, a computer-implemented method, and a non-transitory, computer-readable medium, comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to perform the method, comprising ;
a computing device comprising a processor and a memory; and (Paragraph [0097] computing device has one or more processing device designed to process instructions, for example computer-readable instruction stored on a storage device, Paragraph [0019]; [0097] systems, computer implemented methods, and computer readable media disclosed herein may be useful for generating social media scores):
machine-readable instructions stored in the memory that, when executed by the processor, cause the computing device to at least: (Paragraph [0019]; [0097] storage device may by any type of storage device for example a non-transitory storage device)
train a machine learning model for sentiment analysis of a plurality of social media posts based at least in part on applying a machine learning algorithm to a training data set that comprises a sample text in a format of a respective social media platform, the machine learning model being trained to classify a respective social media post as at least one of positive, negative, or neutral; ([0025-[0026] “The NLP may utilize a Nauve Bayesian classification system to classify the text as either providing a positive, neutral, or negative sentiment…In some embodiments, to evaluate the sentiment of each post a Nauve Bayesian classifier may first be trained on a data set of negative and positive posts. For example, Tweets may be determined to be positive or negative based on emoticon identifiers within the text. Functions may then be performed on the data set to normalize it and extract features (e.g., words or phrases). Normalizing the data may unify the data set and remove redundancies and meaningless text. For example, all text may be lowercased, re-Tweets and hash-tags may be stripped, URLs and HTML may be stripped, and the like. This produces a cleaner dataset with fewer discrepancies (e.g., APPLE and apple would be normalized to be the same), [0033] “may evaluate the sentiment of posts in various other ways. For example, supervised-learning classification algorithms other than Nauve Bayesian classification may be used, such as the Maximum Entropy classifier. Alternatively, the MegaM optimization package or decision trees may be utilized. Still further, classifier voting, which involves training two or more classifiers and choosing the best accuracy between the two, may be used. Combinations and hybrids of these exemplary sentiment models may also be used.”, see also [0048]-[0049])
identify an expiration of a predetermined interval of time for obtaining user submitted content from a social media platform site ([0042]-[0044] “The above described embodiments generate asset scores based on posts accumulated over determined periods of time…posts accumulated within a determined time span. This may be desirable to illustrate the current score (i.e., real-time or near real-time score) of an asset. The score may be periodically (e.g., every determined number of seconds, minutes, hours, days, etc.) logged to allow asset score changes to be observed over time….a user may select a timeframe for relevant posts relating to a topic to be scored…may derive further scoring data, such as the change in an asset's score over a period of time”, [0039] “For each post…repeated until…a determined period of time”)
preprocess the user submitted content by removing a media file from a plurality of user posts to generate a plurality of modified user posts in a plaintext format; ([0026] “For example, Tweets may be determined to be positive or negative based on emoticon identifiers within the text. Functions may then be performed on the data set to normalize it and extract features (e.g., words or phrases). Normalizing the data may unify the data set and remove redundancies and meaningless text. For example, all text may be lowercased, re-Tweets and hash-tags may be stripped, URLs and HTML may be stripped, and the like. This produces a cleaner dataset with fewer discrepancies (e.g., APPLE and apple would be normalized to be the same) – everything but the text/words is stripped and therefore the system removes any media files (e.g., URLs, HTML, images, etc.) from the plurality of user posts to generate a plurality of modified user posts in a plaintext format to use as training data and for input to the model (which is trained to determine sentiment using just the text/words), [0023], see also Paragraph [0019]; [0036-0040]; [0099]; Figs. 2 and 6)
identify a subset of posts with a negative sentiment based at least in part on submitting the plurality of modified user posts to the machine learning model, the subset of posts being returned from the machine learning model in a data structure ([0021]-[0026] & [0019] & [0039]-[0044] & [0099]-[0101] - Any returned subset of posts, any information associated with the returned subset of posts, and any score returned from the machine learning model, is necessarily “in a data structure” (i.e., it is structured data/information within the computer) to enable the server and web/mobile apps to display this information. It is also stored in a database on the server ([0038], [0066]), meaning it is structured.)
determine a negative sentiment score of the subset of posts with the negative sentiment for the interval of time based at least in part on receiving the data structure of the subset of posts; ([0021]-[0026] & [0019] & [0039]-[0044] & [0099]-[0101])
generate an alert in response to the determination that the negative sentiment score exceeds a threshold; ([0084], see also Paragraph [0019]; [0024-0026]; [0035]; [0039-0040]; [0084]; Figs. 2 and 6)
transmit the alert to a client device associated with the recipient, wherein the alert activates a client application executing on the client device to cause the client application to display the negative sentiment score for the alert ([0084], see also Paragraph [0019]; [0024-0026]; [0035]; [0039-0040]; [0084]; Figs. 2 and 6)
connect, across a network, with the client application of the client device to transmit additional information associated with the alert based at least in part on the alert being received by the client device (Vick discloses a web app or other mobile app may provide the interfaces discussed throughout the disclosure ([0083]). As such, the alert (e.g., per [0084]) is presented via one or more user interfaces via this software app. Opening the app via the user device is necessary to display the device. Vick further discloses other functionality that the user may engage with via the app while it is open, such as viewing historic a previous negative sentiment score from a previous period of time ([0043] “s, a user may select a timeframe for relevant posts relating to a topic to be scored. This may allow a user to retrieve a historic score for a period of time of interest”, [0065] “the page sent from the server may include a previously determined score.”, [0100] “real-time graphing 1910 that provides a visual display of the social influence of a given asset or topic. Such an interface may also include a navigation control 1920 configured to allow a user to navigate back in time to see social influence data on a specific asset or topic from past time periods (e.g., weeks, months, or years ago).”). Other information may be dynamically displayed via the app’s interface(s) when it is open ([0042]-[0045] “The score may be periodically (e.g., every determined number of seconds, minutes, hours, days, etc.) logged to allow asset score changes to be observed over time…embodiments may derive further scoring data, such as the change in an asset's score over a period of time, high and low scores and their associated times, inflection points in the rate of change of a score, trending information, and the like. Embodiments may also flag specific social media posts that go viral, thus correlating to significant events relating to an asset's score or posters that have a significant effect on an asset's score. As will be discussed below, graphical models may be generated to provide user interface displays of scores and derived scoring data”, [0056] “The server may then send the score to the client and the score may be displayed in the page for viewing by a user. This constant flow may only add a few milliseconds of delay to loading a page while allowing users to receive live scores for a requested assets and social media content aggregated and normalized from plural networks.”, [0075] “FIG. 12 also includes user interface controls 930 to allow a user to browse historic posts (e.g., new posts may appear from the left”). In both instances, the client application of the client device (that is open, as is required to display the received alert – therefor based at least in part on the alert being received by the client device) is connecting across the network with the server to receive additional information associated with the alert (e.g., historic data, historic scores, associated post data, related trends/metrics associated in some with the alert).)
Vick does not appear to disclose,
determine the negative sentiment score exceeds a first moving average sentiment score; and generate an alert in response to the determination that the negative sentiment score exceeds the first moving average sentiment score
format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging a recipient…transmit the alert …based at least in part on the alert being formatted; and
halt the alert at the client device by instructing the client device to cease to display the alert on the client device based at least in part on a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score
However, Bala discloses
determine the negative sentiment score exceeds a first moving average sentiment score; and generate an alert in response to the determination that the negative sentiment score exceeds the first moving average sentiment score ([0137] & [0140] & [0169] & [0226] & [0319], see also [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21)
format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging a recipient…transmit the alert …based at least in part on the alert being formatted; and ((Paragraph [0128] “alerts may be delivered to the consumer by any known route (e.g. email, text message, pop-up, phone call, or through a mobile application. The consumer may define how they consumer wishes to receive the alert. The consumer may define which alerts the consumer wishes to receive, and/or thresholds for providing alerts” see also [0157]; [0163-0164]; Figs. 19-21)
halt the alert at the client device based at least in part on a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window. The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time. To provide an indication that a trend may be changing, or if a trend is deviating from a trend of another index associated with an entity, a consumer may obtain alerts when these triggers are detected. (The examiner notes that the broadest reasonable interpretation of halting an alert would include only obtaining an alert while specified triggers are detected, such as if a trend is no longer deviated from a trend of another index the consumer would not obtain alerts)).
Bala suggests it is advantageous to determine the negative sentiment score exceeds a first moving average sentiment score; and generate an alert in response to the determination that the negative sentiment score exceeds the first moving average sentiment score, format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging a recipient…transmit the alert …based at least in part on the alert being formatted; and, and halt the alert at the client device based at least in part on a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes and because doing so can enable the recipient to receive alerts in a desired format (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to determine the negative sentiment score exceeds a first moving average sentiment score; and generate an alert in response to the determination that the negative sentiment score exceeds the first moving average sentiment score, format the alert to fit within a data allotment based at least in part on the data allotment being associated with a specified messaging a recipient…transmit the alert …based at least in part on the alert being formatted; and, and halt the alert at the client device based at least in part on a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score, as taught by Bala, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes and because doing so can enable the recipient to receive alerts in a desired format.
Vick and Bala do not appear to disclose,
halt the alert at the client device by instructing the client device to cease to display the alert on the client device
However, Bailey discloses a method and system for tracking sentiment by analyzing a subset of social media posts ([0005]-[0010]) using trained machine learning model(s) ([0046]), identifying an expiration of a predefined interval of time for obtaining user submitted content from a social media platform cite ([0127]-[0128]), and configuring various user-defined conditions/thresholds for triggering sentiment-based alerts (Figs 15A-15M) that are presented via GUIs on a web app ([0025]-[0027] & [0033] & [0114]-[0116]), including wherein alerts are triggered in response to sentiment deviation thresholds (e.g., a certain deviation of sentiment for a current time window deviating from a previous sentiment for a previous time window, such as a second moving average sentiment score (for a current time window) being less than a respective threshold value associated with a first moving average sentiment score (for the previous time window)) (Fig 15D and corresponding sections [0128]-[0134] & [0161]-[0162] show configurable sentiment deviation thresholds as well as difference from norm thresholds which are defined based on moving average sentiment scores/values relative to the moving average sentiment scores/values of the preceding time period). Bailey further disclsoes
halt the alert at the client device by instructing the client device to cease to display the alert on the client device ([0156] “Alert space 1530 provides a continuously updated table 1532” and [0119] “alert…interval duration…requested time period…” and [0127]-[0133] “requested time period specifies the time period for which message sets are to be examined…the time period determines whether the topic group requests…an alert…” – also the Gui of the alert space is provided in a web app ([0025]-[0027] & [0033] & [0114]-[0116]) and the alerts are triggered in response to sentiment deviation thresholds (e.g., a certain deviation of sentiment for a current time window deviating from a previous sentiment for a previous time window, such as a second moving average sentiment score (for a current time window) being less than a respective threshold value associated with a first moving average sentiment score (for the previous time window)) (Fig 15D and corresponding sections [0128]-[0134] & [0161]-[0162] show configurable sentiment deviation thresholds as well as difference from norm thresholds which are defined based on moving average sentiment scores/values relative to the moving average sentiment scores/values of the preceding time period)) and therefore the interface would remove an alert as it is continually updated by instructing the client device to cease to display the alert on the client device (e.g., in response to a second moving average sentiment score that is less than a respective threshold value associated with the first moving average sentiment score), see
Bailey suggests it is advantageous to halt the alert at the client device by instructing the client device to cease to display the alert on the client device, because doing so can ensure the graphical user interface on which user-configurable sentiment alerts are displayed is updated such that the alerts being displayed are current and aligned with the trigger/display criteria specified by the user (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick in view of Bala to halt the alert at the client device by instructing the client device to cease to display the alert on the client device, as taught by Bailey, because doing so can ensure the graphical user interface on which user-configurable sentiment alerts are displayed is updated such that the alerts being displayed are current and aligned with the trigger/display criteria specified by the user.
With respect to claims 2, 9, and 16, Vick, Bala, and Bailey teach the system of claim 1, the method of claim 8, and the non-transitory, computer-readable medium of claim 15. Vick does not appear to disclose,
wherein the first moving average sentiment score is a moving average of the negative sentiment score for a defined preceding time period
However, Bala discloses
wherein the first moving average sentiment score is a moving average of the negative sentiment score for a defined preceding time period ([0137] & [0140] & [0169] & [0226] & [0319], see also [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21)
Bala suggests it is advantageous to include wherein the first moving average sentiment score is a moving average of the negative sentiment score for a defined preceding time period; because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to include wherein the first moving average sentiment score is a moving average of the negative sentiment score for a defined preceding time period, as taught by Bala, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes.
Examiner notes that Bala and Bailey also teach this limitation.
With respect to claims 4, 11, and 18, Vick, Bala, and Bailey teach the system of claim 1, the method of claim 8, and the non-transitory, computer-readable medium of claim 15. Vick does not appear to disclose,
determine an alert time interval has passed since the transmission of the alert to the client device;
compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and
However, Bala discloses
determine an alert time interval has passed since the transmission of the alert to the client device; (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window, by most recent time the threshold is exceeded, or any combination thereof. (The examiner notes that the broadest reasonable interpretation of calculating a second moving average sentiment score after an alert was initiated would include determining an index change within a fixed or moving window of time triggered after the most recent time a threshold was exceeded). The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time)
compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window. The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time. To provide an indication that a trend may be changing, or if a trend is deviating from a trend of another index associated with an entity, a consumer may obtain alerts when these triggers are detected)
Bala suggests it is advantageous to determine an alert time interval has passed since the transmission of the alert to the client device; and compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an alert (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to determine an alert time interval has passed since the transmission of the alert to the client device; and compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score, as taught by Bala, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an.
Examiner notes that Bailey also teach this limitation.
With respect to claims 5, 12, and 19, Vick, Bala, and Bailey teach the system of claim 1, the method of claim 8, and the non-transitory, computer-readable medium of claim 15. Vick does not appear to disclose,
in response to the alert being triggered, calculate a second moving average sentiment score, the second moving average sentiment score representing a moving average of the negative sentiment score since the alert was initiated;
compare the first moving average sentiment score to the second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and
However, Bala discloses
in response to the alert being triggered, calculate a second moving average sentiment score, the second moving average sentiment score representing a moving average of the negative sentiment score since the alert was initiated; (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window, by most recent time the threshold is exceeded, or any combination thereof. (The examiner notes that the broadest reasonable interpretation of calculating a second moving average sentiment score after an alert was initiated would include determining an index change within a fixed or moving window of time triggered after the most recent time a threshold was exceeded). The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time)
compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window. The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time. To provide an indication that a trend may be changing, or if a trend is deviating from a trend of another index associated with an entity, a consumer may obtain alerts when these triggers are detected)
Bala suggests it is advantageous to include wherein the moving average sentiment score is a first moving average sentiment score and the machine-readable instructions further cause the computing device to at least: in response to the alert being triggered, calculate a second moving average sentiment score, the second moving average sentiment score representing a moving average of the negative sentiment score since the alert was initiated; compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and halt the alert in response to a determination that the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an alert (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to include wherein the moving average sentiment score is a first moving average sentiment score and the machine-readable instructions further cause the computing device to at least: in response to the alert being triggered, calculate a second moving average sentiment score, the second moving average sentiment score representing a moving average of the negative sentiment score since the alert was initiated; compare the first moving average sentiment score to a second moving average sentiment score to determine whether the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score; and halt the alert in response to a determination that the second moving average sentiment score is less than a threshold value that is based at least in part on the first moving average sentiment score, as taught by Bala, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an alert.
Examiner notes that Bailey also teach this limitation.
With respect to claims 6 and 13, Vick, Bala, and Bailey teach the system of claim 1 and the method of claim 8. Vick does not appear to disclose,
recalculate the negative sentiment score for the subset of posts associated with the social media platform within the predefined interval of time;
compare the recalculated negative sentiment score to the first moving average sentiment score to determine whether the recalculated negative sentiment score is less than the threshold value, the threshold value being based at least in part on the first moving average sentiment score; and
However, Bala discloses
recalculate the negative sentiment score for the subset of posts associated with the social media platform within the predefined interval of time; (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window, by most recent time the threshold is exceeded, or any combination thereof. (The examiner notes that the broadest reasonable interpretation of calculating a second moving average sentiment score after an alert was initiated would include determining an index change within a fixed or moving window of time triggered after the most recent time a threshold was exceeded). The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time)
compare the recalculated negative sentiment score to the first moving average sentiment score to determine whether the recalculated negative sentiment score is less than the threshold value, the threshold value being based at least in part on the first moving average sentiment score (Paragraph [0003-0004]; [0085] [0125-0128]; [0157]; [0163-0164]; Figs. 19-21, methods and systems are provided for assessing and providing long-term indicators of sentiment. Additional benefit may be provided when assessing the aggregate sentiments in the context of similar areas of interest and/or over stretches of time. This invention relates to a method and system for the generation of a long-term numerical index that provides an enhanced metric reflecting sentiment associated with rapidly changing indications of sentiment. As an additional preferred embodiment, the general sentiment score for an area of interest, categorical or overall, is intended to reflect a continuous quantitative sentiment index, updated frequently, reflecting behavior in the areas of interest. The objective of the index is to provide an indication of the movement of the sentiment over time regarding the categorical or overall area of interest. To depict aggregate temporal behavior of the index over selectable windows of time, a preferable embodiment of the invention enables the consumer to view a curve representing the moving average of the index over time. A skilled artisan can appreciate the use of known mathematical techniques for computing the simple moving average, the cumulative moving average, the weighted moving average, and the exponential moving average. Any or all of these are applicable in displaying moving average behavior of a sentiment index to a consumer in conjunction with the temporal behavior of the sentiment index. To further inform temporal behavior of the index over selectable windows of time, a preferred embodiment enables the consumer to view or receive alerts indicating index changes within fixed, moving, or dynamically expandable windows of time triggered by fixed, moving, or dynamically expandable thresholds keyed from the start of the time window. The consumer may define which alerts the consumer wishes to receive and/or thresholds for providing alerts. The consumer may define the time window, such as a start and/or end time. To provide an indication that a trend may be changing, or if a trend is deviating from a trend of another index associated with an entity, a consumer may obtain alerts when these triggers are detected)
Bala suggests it is advantageous to include wherein the machine-readable instructions further cause the computing device to at least: recalculate the negative sentiment score for the plurality of user posts to the social media platform within the predefined interval of time; compare the recalculated negative sentiment score to the moving average sentiment score to determine whether the recalculated negative sentiment score is less than the threshold value, the threshold value being based at least in part on the moving average sentiment score; and halt the alert in response to a determination that the recalculated negative sentiment score is less than the threshold value, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an alert (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to include wherein the machine-readable instructions further cause the computing device to at least: recalculate the negative sentiment score for the plurality of user posts to the social media platform within the predefined interval of time; compare the recalculated negative sentiment score to the moving average sentiment score to determine whether the recalculated negative sentiment score is less than the threshold value, the threshold value being based at least in part on the moving average sentiment score; and halt the alert in response to a determination that the recalculated negative sentiment score is less than the threshold value, as taught by Bala, because doing so can help to determine and track the sentiment of users towards a product or company over time and detect significant spikes/changes that may warrant an.
Examiner notes that Bailey also teach this limitation.
With respect to claims 7 and 14, Vick, Bala, and Bailey teach the system of claim 6 and the method of claim 13. Vick does not appear to disclose,
wherein the alert is halted by further causing the computing device to at least: transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient
However, Bala discloses
wherein the alert is halted by further causing the computing device to at least: transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient ([0140] & [0169] )
Bala suggests it is advantageous to include wherein the alert is halted by further causing the computing device to at least: transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient; because doing so can inform an entity that they do not need to worry about the sentiment any longer (see citations above).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick to include wherein the alert is halted by further causing the computing device to at least: transmit a subsequent email or a subsequent SMS message to the client device associated with the recipient, as taught by Bala, because doing so can inform an entity that they do not need to worry about the sentiment any longer.
With respect to claim 21, Vick teaches the medium of claim 15,
wherein the machine-readable instructions that connect, across the network, with the client application of the client device to transmit additional information further cause the computing device to at least: enable access for the client device to view a previous negative sentiment score from a previous period of time stored in a memory associated with the computing device ([0043] “ a user may select a timeframe for relevant posts relating to a topic to be scored. This may allow a user to retrieve a historic score for a period of time of interest”, [0065] “the page sent from the server may include a previously determined score.”, [0100] “real-time graphing 1910 that provides a visual display of the social influence of a given asset or topic. Such an interface may also include a navigation control 1920 configured to allow a user to navigate back in time to see social influence data on a specific asset or topic from past time periods (e.g., weeks, months, or years ago).”).
v Claims 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Vick in view of Bala in view of Bailey as applied to claims 1, 8, and 15 above, and further in view of Aamir et al. (U.S. PG Pub No. 2014/0013223 January 9, 2014- hereinafter "Aamir”)
With respect to claims 3, 10, and 17, Vick, Bala, and Bailey teach the system of claim 1, the method of claim 8, and the non-transitory, computer-readable medium of claim 15. Vick further discloses
wherein the machine-readable instructions that cause the computing device to determine the negative sentiment score further causes the computing device to at least: for each post in the subset of posts with the negative sentiment, identify a number of reposts the post and a number of likes associated with the post ([0099] “real-time sentiment classification 1830 may include…Facebook likes, re-tweets”, see also the table in [0054]),
As discussed above with respect to the independent claims, Vick discloses a system that may score assets (topics, brands, etc.) based on analyzing posts associated with that asset over a certain time period (i.e., a subset of posts) including determining the sentiment of those posts as well as various metrics associated with those posts (see [0021]-[0025] & [0041] & [0045] & [0056]). Vick discloses that the score may represent a sentiment (e.g., negative sentiment) of the asset based on the subset of posts, and that the score may be calculated in a variety of different ways, including several ways that include calculating the score based on the volume of the posts and reach of the posts (see [0039]-[0041] & [0045] & [0056]). Volume of posts about the asset is the number of posts in the subset of posts (e.g., with the negative sentiment). Although Vick suggests the system may determine the score in a variety of different ways to capture the potential impact of the subset of posts including using the volume, and although the system may track the number of likes of each post in the subset of posts (see table in [0054] and [0099]) as well as reposts ([0099] “re-tweets”), Vick does not appear to explicitly disclose wherein the score is calculated by summing the number of reposts of the posts in the subset with the number of likes associated with each post in the subset of posts with the volume. Vick does not appear to disclose,
calculate a sum of the posts in the subset of posts with the negative sentiment and the number of reposts and the number of likes associated each post in the subset of posts with the negative sentiment, wherein the sum represents the negative sentiment score
However, Aamir discloses a system for determining sentiment and sentiment-related metrics for content (abstract, [0013], [0020]) to enable entities to understand current/trending sentiment regarding topics of interest to enable them to respond accordingly or mitigate the damage of negative sentiment ([0003], [0013], [0017]). Aamir suggest that a subset of content units (posts) related to the topic can be analyzed to generate metrics or visualizations associated with the sentiment ([0004]-[0005]). Aamir discloses wherein one of the metrics associated with the polarity (e.g., negative sentiment) of the content unit(s) is virality, which is therefore a negative sentiment score (it represents a spread of posts/information that have negative polarity/sentiment across the network) ([0013] & 0044]-[0049] & Claim 6 “generate a plot…visualizing the polarity and the at least one other metric…wherein the at least one other metric is…virality”) , and that virality comprises a sum of likes and shares (i.e., reposts, consistent with Applicant’s own disclosure at [0046] as consistent with the plain meaning of the word in the art) for the content units (post(s) with the negative sentiment). Aamir discloses
calculate a sum of the posts in the subset of posts with the negative sentiment and the number of reposts and the number of likes associated each post in the subset of posts with the negative sentiment, wherein the sum represents the negative sentiment score ([0044] “determine virality for each content unit. A viral count comprises the sum of all social media comments, likes, shares, views, etc. for the content unit within its respective recency unit” & [0004] “collect one or more content units from one or more content sources; (b) determine whether each content unit relates to a topic; (c) determine a polarity for each content unit and at least one other metric relating to the content unit; and (d) generate a plot comprising a plurality of data points for visualizing the polarity and the at least one other metric of the one or more respective content units”)
Aamir suggests it is advantageous to include calculating a sum of the posts in the subset of posts with the negative sentiment and the number of reposts and the number of likes associated each post in the subset of posts with the negative sentiment, and wherein the sum represents the negative sentiment score, because doing so can inform an accurate indication of the virality of the sentiment which captures a potential impact of the subset of posts ([0004]-[0005] & [0044]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system, method, and media of Vick in view of Bala to include calculating a sum of the posts in the subset of posts with the negative sentiment and the number of reposts and the number of likes associated each post in the subset of posts with the negative sentiment, and wherein the sum represents the negative sentiment score, as taught by Aamir, because doing so can inform an accurate indication of the virality of the sentiment which captures a potential impact of the subset of posts.
Furthermore, since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself. That is in the substitution of the negative sentiment score/metric of Aamir (i.e., calculating a sum of the posts in the subset of posts with the negative sentiment and the number of reposts and the number of likes associated each post in the subset of posts with the negative sentiment, and wherein the sum represents the negative sentiment score) for the negative sentiment score/metric of Vick in view of Bala (e.g., various other combinations of the sentiment, reach, and volume of posts about a given asset, such as sentiment x reach x volume).Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure.
Rasmussen et al. (U.S. Patent No. 12,271,913, April 8, 2025) teaches analyzing social media posts to identify sentiment trends and issuing corresponding alerts
DeLuca et al. (U.S. PG Pub No. 2018/0060338, March 1, 2018) teaches analyzing social media posts to identify sentiment trends and issuing corresponding alerts.
Chhaya et al. (U.S. PG Pub No. 2015/0149373, May 28, 2015) teaches analyzing social media posts to identify sentiment trends and issuing corresponding alerts.
Conclusion
No claim is allowed
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES M DETWEILER whose telephone number is (571)272-4704. The examiner can normally be reached on Monday-Friday from 8 AM to 5 PM ET.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraf can be reached at telephone number (571)-270-3948. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/JAMES M DETWEILER/Primary Examiner, Art Unit 3621
Prosecution Insights