Abstract: A processing system uses a set of rules that identify a set of keywords and stores a set of creative images associated with the keywords. The processing system identifies metrics for the social media that includes the keywords and displays the creative images associated with the keywords with the largest social media metrics. The set of rules may include promotions to display with the creative content and filters that determine what social media to use to generate the metrics. No manual curation of content is necessary. The processing system saves time and effort as well as taps into real time consumer trends.

Abstract: A content compliance system uses machine learning to generate objective verification that content complies with brand criteria. The content compliance system may force the company to select specific brand criteria listed on a user interface. The selected brand criteria are then readily displayed to the creative agency. The content compliance system then compares the selected brand criteria with content generated by the creative agency. The content compliance system uses machine learning algorithms to generate a compliance score that provides a real-time objective indication of the compliance of the creative content with the selected brand criteria. The creative agency can then modify the creative content and receive a real-time updated compliance score.

Abstract: A content compliance system uses machine learning to generate objective verification that content complies with brand criteria. The content compliance system may force the company to select specific brand criteria listed on a user interface. The selected brand criteria are then readily displayed to the creative agency. The content compliance system then compares the selected brand criteria with content generated by the creative agency. The content compliance system uses machine learning algorithms to generate a compliance score that provides a real-time objective indication of the compliance of the creative content with the selected brand criteria. The creative agency can then modify the creative content and receive a real-time updated compliance score.

Abstract: An organization mapping system reverse engineer's online data from websites and social network accounts into an organization map representing brands owned by a company. The mapping system extracts objects from the online data associated with different brands, products, services, campaigns, locations, events, etc. The mapping system organizes the objects into an organization map that can be used to automatically configure enterprise software. The organization map necessarily includes the most recent and up-to-date brands, products, and campaigns operating within a company and is therefore inherently more accurate than current organization mapping techniques.

Abstract: A control center includes a display screen for displaying different social media and social media analytics. The control center includes an enhanced notification device that operates independently and remotely from the display screen. A media controller receives a selection of a search term, selection of an analytic, and selection of a trigger event for the analytic. The control center obtains social media from different networks containing the search term and generates the selected analytic from the social media. The media controller activates the enhanced notification device when the trigger event is detected in the analytic. The activated notification device provides a different environmental attribute than the display screen that is more effective in gaining the attention of the control center operators.

Abstract: A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be generated using a mutual information topic distribution model.

Abstract: A dialogue intent analyzer uses a conversation between a user and agent, and intents in the conversation to predict a set of answers that better respond to pending user question. The dialogue intent analyzer understands the context surrounding the pending question by capturing and modeling prior conversation and intents within the conversation. Dialogue intent analyzer also reduces genericness in predicted answers by weighting previously used answers based on their frequency and length. Dialogue intent analyzer also increases diversity of predicted answers by using a diverse beam search.

Abstract: A command center provides ad-hoc search and navigation through different dimensional topic levels that allow users to better analyze and correlate data. The command center not only generates and displays content and metrics associated with an event, but can also generate and display real-time content and metrics for other topics, products, and/or services related to a currently displayed topic. The command center enables a user to navigate through the different dimensional levels simply by selecting items displayed by a remote control application. The command center also automatically synchronizes the content and metrics for any selected dimension to a same corresponding time period.

Abstract: An insight system identifies brands, subjects, attributes, and the sentiment conveyed for those attributes. The insight system pairs the attributes with the subjects and brands and generates metrics based on the sentiments associated with the attributes. The insight system may parse product webpages linked to the content for brand identifiers and associate the brand identifiers with the brands. The insight system provides more granular insight into user sentiment for different features associated with the brands.

Abstract: A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be generated using a mutual information topic distribution model.

Abstract: A command center provides ad-hoc search and navigation through different dimensional topic levels that allow users to better analyze and correlate data. The command center not only generates and displays content and metrics associated with an event, but can also generate and display real-time content and metrics for other topics, products, and/or services related to a currently displayed topic. The command center enables a user to navigate through the different dimensional levels simply by selecting items displayed by a remote control application. The command center also automatically synchronizes the content and metrics for any selected dimension to a same corresponding time period.

Abstract: A system and method that enables usage of data embedded inside social media data to help estimate buy intent (BI), to allow companies or organizations to utilize this information to track conversations about their brand, to engage with their customers/users, to conduct advisement and investment efficiency analysis, to manage and reduce potential risk, and identify the factors that may affect company sales and revenues.

Abstract: A display server automatically determines layouts of display walls. The display server receives one or more setup messages from a display wall and assigns one or more universal resource locators (URLs) to one or more display screens in the display wall based on the setup messages. The display server sends one or more webpages including different patterns to display on the display screens in the display wall and receives back display information showing the patterns displayed on the display screens. The display server then generates a configuration file identifying an arrangement of display regions in the display wall based on the display information. The display server also may operate a content manager that accesses the configuration file to identify the layouts for the different display walls and identify storyboards with similar layouts.

Abstract: An object-oriented data management method and system comprising nested structural-elements that form inter-related containers of IRC-Infoids that include information, processing-rules, and an atomic-action layer, enabling functions to operate across disparate-systems using self-normalizing data-definitions is disclosed. The creation and management of the IRC-Infoid objects, rules and actions are handled by an IRC-Infoid Engine. The IRC-Infoid is an object with its own definitions, properties, and rules, related to a single parent element. Six properties define the IRC-Infoid: event, user, file, message, data and relationship. These properties follow inter-relationship rules, which force internal consistency, data optimization, and maintain data integrity. The IRC-Infoid data structure includes documentation, thought leadership and chatter, which when parsed through the rule sets, gets attached to standard or triggered actions, including periodic updates and called actions for use across disparate systems.

Abstract: A dialogue intent analyzer uses a conversation between a user and agent, and intents in the conversation to predict a set of answers that better respond to pending user question. The dialogue intent analyzer understands the context surrounding the pending question by capturing and modeling prior conversation and intents within the conversation. Dialogue intent analyzer also reduces genericness in predicted answers by weighting previously used answers based on their frequency and length. Dialogue intent analyzer also increases diversity of predicted answers by using a diverse beam search.

Abstract: A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be generated using a mutual information topic distribution model.

Abstract: A control center includes a display screen for displaying different social media and social media analytics. The control center includes an enhanced notification device that operates independently and remotely from the display screen. A media controller receives a selection of a search term, selection of an analytic, and selection of a trigger event for the analytic. The control center obtains social media from different networks containing the search term and generates the selected analytic from the social media. The media controller activates the enhanced notification device when the trigger event is detected in the analytic. The activated notification device provides a different environmental attribute than the display screen that is more effective in gaining the attention of the control center operators.

Abstract: An operator enters a name of a company, product, or any other entity into a user interface. A hashtag analytic system then automatically discovers social media campaigns associated with that entity based on hashtag or keyword usage in associated posted messages. The hashtag analytic system may automatically discover the social media accounts for the entity and then scan messages posted on the social media accounts for hashtags. The hashtag analytic system groups together posted messages that include campaign related hashtags and generates analytics for the groups of messages associated with the same campaigns.

Abstract: A command center provides ad-hoc search and navigation through different dimensional topic levels that allow users to better analyze and correlate data. The command center not only generates and displays content and metrics associated with an event, but can also generate and display real-time content and metrics for other topics, products, and/or services related to a currently displayed topic. The command center enables a user to navigate through the different dimensional levels simply by selecting items displayed by a remote control application. The command center also automatically synchronizes the content and metrics for any selected dimension to a same corresponding time period.

Abstract: A conversation correlation system is configured to associate social signals with conversations and group the conversations into topic clusters. The topic clusters for different days are linked together to form conversation streams. The conversation streams may identify conversation topics within ecosystems and identify changes in conversation topics over time. Topic labels may be generated for the topic clusters that better describe conversation topics. In one example, the topic labels may be generated using a mutual information topic distribution model.