Abstract: A method, computer system, and computer program product for petition creation through social analytics are provided. The embodiment may include generating a repository of user social data. The embodiment may also include extracting one or more social topics that are related to the user social data. The embodiment may further include generating a social supplication model using the repository and the extracted social topic. The embodiment may also include determining discussion issues within the social topic and a topic discussion distance between each user based on the generated social supplication model. The embodiment may further include generating a petition based on a determined discussion issue.

Abstract: An approach for directing a chat agent for an online discussion is provided. A processor retrieves message data from a messaging program. A processor identifies at least one topic present in the message data. A processor, responsive to a determination that the at least one topic is a primary topic, updates the chat agent with the primary topic. A processor modifies message data based on the determined primary topic.

Abstract: Content propagation control can include determining a classification of a message formatted for conveyance over a data communications network. The classification can be based on content of the message and determined using a classification model constructed by analyzing prior message propagation rates and corresponding propagation paths that are each associated with one of multiple message content types. Content propagation control also can include selecting propagation rate and propagation path control indicators based on the classification of the message determined using the classification model and embedding the propagation rate and propagation path control indicators in the message.

Abstract: Computer-implemented methods, computer program products, and computer systems for mitigating frequency loss may include one or more processors configured for receiving first audio data corresponding to unobstructed user utterances, receiving second audio data corresponding to first obstructed user utterances, generating a frequency loss (FL) model representing frequency loss between the first audio data and the second audio data, receiving third audio data corresponding to one or more second obstructed user utterances, processing the third audio data using the FL model to generate fourth audio data corresponding to a frequency loss mitigated version of the second obstructed user utterances, and transmitting the fourth audio data to a recipient computing device. The first obstructed user utterances are obstructed by a facemask and the one or more second obstructed user utterances is obstructed by the facemask. The FL model may be executed as an audio plugin in a web conferencing program.

Abstract: Disclosed are techniques to model when authoritative responses are expected to be received in real-time chat dialogues to facilitate monitoring a live real-time chat and connect a participant to provide an authoritative answer at an appropriate time during the live real-time chat. Historical real-time chat dialogues are used to generate a model for when authoritative responses are expected in real-time chats. A live real-time chat is monitored for an ongoing discussion without an authoritative response, and a response latency window of the model for the live real-time chat is adjusted based on the ongoing discussion in the live real-time chat. In some embodiments, upon entering an optimal window of the ongoing discussion of the live real-time chat indicated by the model where it is determined that no authoritative response is yet received, a new participant is connected to the live real-time chat to provide an authoritative response.

Abstract: A computer-implemented method and system for arranging, in an ordered hierarchy, attached files as transferred during a discourse history. The computer implemented method includes accessing discourse data associated with a history of discourse communications. In embodiments, the discourse data includes a plurality of discourse attachments transferred in accordance with the history, and the discourse attachments include multiple versions of at least one discourse attachment within the plurality. The method further includes deriving a discourse attachment arrangement (DAA) component based at least in part on the discourse data. The method includes outputting, based at least in part on the DAA component, the multiple versions of the at least one discourse attachment arranged in a hierarchical order.

Abstract: In response to determining that a native language of a first user is different from a target language of a message to be transmitted by the first user to a second user, a translation model based on a plurality of language efficacies of the first user is created. An optimal action associated with a translation of the message from the native language to the target language is determined based on the created model and a language efficacy of the first user in the native language. The determined optimal action is performed. The message translation comprising the performed optimal action is transmitted to the second user.

Abstract: Disclosed embodiments provide techniques for estimating the accuracy of a user rating score. In embodiments, a user rating score is obtained from a user. Online activity events such as social media posts, purchases, cancellations, online reviews, and/or other activities are analyzed by a computer system to determine a level of agreement between the score the user provided, and the online activity events of the user that pertain to the product and/or service to which the score pertains. A user rating score reliability factor is computed based on the level of agreement and can be made available to stakeholders such as product managers, marketing personnel, and sales teams.

Abstract: Providing learned interactions in a virtual reality or augmented reality (collectively, a computer-mediated reality) can include determining a probable physical action of a user interacting with a computer-mediated reality (CMR) environment. A learned interaction corresponding to the probable physical action can be generated based on a CMR-physical action (CMRPA) model that correlates physical actions with results of the physical actions in a CMR scenario of the CMR environment. In response to determining, based on at least one identified characteristic of the user, a statistical likelihood of benefiting the user by providing the learned interaction, a learned interaction corresponding to the probable physical action can be provided to the user.

Abstract: A ticket relating to a software event is received in a software development system. One or more public forums on software development is searched for the software event. Two or more topics on the software event are identified from one or more conversations from the one or more public forums that regard the software event. Two or more causes of the software event are determined by analyzing interrelations of the two or more topics.

Abstract: Self-executing document revision includes creating a current version of an electronic rendering of a collaborative document based on input received from a user via a communicative coupling with a data communications network. The current version's relevancy is determined by a self-executing document revisor and compared with the relevancy of a prior version of the collaborative document. In response to determining the relevancy of the current version is less than the relevancy of the prior version, one or more segments of one or more electronically stored versions of the collaborative document are selected based on a relevancy of each of the one or more segments, the relevancy of each determined by the self-executing document revisor. The self-executing document revisor generates a graphical representation of a revised version of the collaborative document by merging the one or more segments selected with the current version of the collaborative document.

Abstract: Disentanglement of chat utterances is provided. An analysis of the linguistic collocations and the keywords of the multiple chat utterances and amount of contribution by respective chat users of the plurality of chat users to the multiple chat utterances is performed to determine a level of drift of the linguistic collocations, the keywords, and respective chat users over a course of the multiple chat utterances. Chat utterance entanglement of prior chat utterances is determined using determined level of drift based on the analysis by inferring keyword usage over time and how these keywords are related over the course of the multiple chat utterances. The prior chat utterances related to a particular topic are disentangled by removing certain chat utterances that have a statistically significant level of drift from that particular topic. Removed chat utterances are arranged as a new chat discourse related to a different topic in the chat conversation.

Abstract: A computer receives reviews for an item from a plurality of sources. The computer may identify one or more key features of the item. The computer collects user preferences for the one or more key features of the item. The computer calculates odds ratio for each of the one or more key features of the item. The computer determines an affinity measure for each of the one or more key features based on the calculated odds ratio for each of the one or more key features of the item; and generates a forest plot for the item, where the forest plot comprises a summary measure determined using the affinity measure for each of the one or more key features.

Abstract: One embodiment of the present invention provides a method comprising running a monitoring agent on a connected electronic device, and determining, via the monitoring agent, a level of hearing impairment of an individual user associated with the connected electronic device. The method further comprises, in response to determining the individual user has some level of hearing impairment, selecting a notification mechanism suitable for notifying the individual user based on the level of hearing impairment, and invoking the monitoring agent to notify the individual user of an event in accordance with the notification mechanism selected.

Abstract: In an approach to training a corpus link model and generating collocated terms for intra-channel and inter-channel activity, one or more computer processors train a corpus link model based on an analysis of a linguistic corpus and an analysis of one or more author metrics. The one or more computer processors generate one or more collocated terms based on one or more calculations by the trained corpus link model. The one or more computer processors generate a co-occurrence rating for each of the one or more generated collocated terms. The one or more computer processors display the one or more generated collocated terms according to the generated co-occurrence rating of each collocated term.

Abstract: An embodiment of a summarization application divides collected conversation data into media and text components. The application implements respective machine learning mechanisms to enhance modeling operations of the text and media components to identify key elements from the conversation. The application generates a headline banner from a group of key elements based on an analysis involving first predetermined criteria. The application also combines additional key elements to the group of key elements to form a second group of key elements. The application generates a summary from the second group of key elements based on a second analysis involving second predetermined criteria. The application presents, via a display, the headline banner according to a first output of the first key element analysis and the summary according to a second output of the second key element analysis.

Abstract: Self-executing document revision includes creating a current version of an electronic rendering of a collaborative document based on input received from a user via a communicative coupling with a data communications network. The current version's relevancy is determined by a self-executing document revisor and compared with the relevancy of a prior version of the collaborative document. In response to determining the relevancy of the current version is less than the relevancy of the prior version, one or more segments of one or more electronically stored versions of the collaborative document are selected based on a relevancy of each of the one or more segments, the relevancy of each determined by the self-executing document revisor. The self-executing document revisor generates a graphical representation of a revised version of the collaborative document by merging the one or more segments selected with the current version of the collaborative document.

Abstract: A processor may receive congregation data. The congregation data may be associated with a particular area. The processor may analyze the congregation data. The processor may generate a social movement model of the particular area. The processor may generate one or more routes from a first location to a second location in the particular area based on the social movement model. The one or more routes may reduce the level of exposure to an infectious disease.

Abstract: In an approach to collaborative discourse, responsive to receiving a collaborative discourse, a document corpora of the collaborative discourse is analyzed. A picture metadata is analyzed for each image in a graphic repository. A machine learning model is derived based on the analysis of the document corpora and the analysis of the picture metadata. Appropriate images are selected from the graphic repository based on the machine learning model, where the appropriate images closely align with the collaborative discourse.

Abstract: In an approach, a processor detects at least one training message delivered by a user on a social media application, the training message being accessible by an operator. A processor records training feedback performed by the operator on the social media application regarding to the at least one training message. A processor trains an analysis engine module using (i) the at least one training message as input and (ii) the training feedback as output. A processor generates a predicted feedback for a subsequent message based on the trained analysis engine module.