Abstract: A method and a system for generating a search query to extract one or more relevant messages from a plurality of messages shared over a computer network. The method includes extracting a plurality of keywords and information pertaining to a plurality of customers from the plurality of messages. Further, the method identifies a set of influential customers from the plurality of customers based on a first score and a second score. The method further includes extracting a set of influential keywords from a first set of messages based on a first number of occurrences of the plurality of keywords in the plurality of messages within a pre-defined time interval. The method further includes generating the search query that includes at least the set of influential customers and the set of influential keywords.

Abstract: The disclosed embodiments illustrate methods and systems for processing social media data for content recommendation to a user. The method includes extracting a set of entity data from the social media data of the user. The method further includes extracting semantic data of each entity data in the extracted set of entity data from one or more knowledge databases over a communication network. The method further includes generating a user-interest vector of the user. The user-interest vector of the user is generated based on at least a mapping of the extracted semantic data of each entity data with one or more leaf nodes in an interest taxonomy. The generated user-interest vector is further utilized for recommending targeted content to the user.

Abstract: A first embodiment of the disclosure relates to a method for responding to a message posted in a social media stream. The method includes monitoring a social media site for at least one message including select subject matter. In response to identifying a message, the method includes collecting a series of exchanges that form a conversational thread including the message. The method includes determining at least one content attribute of the message. The method includes classifying the message using at least one key attribute. The method includes searching a database for a reference message using a combination of the at least one content and key attributes. The method includes determining a previous outcome of a reference thread including the reference message. The method includes using the previous outcome for determining a course of action.

Abstract: The disclosed embodiments illustrate methods and systems for processing social media data for content recommendation to a user. The method includes extracting a set of entity data from the social media data of the user. The method further includes extracting semantic data of each entity data in the extracted set of entity data from one or more knowledge databases over a communication network. The method further includes generating a user-interest vector of the user. The user-interest vector of the user is generated based on at least a mapping of the extracted semantic data of each entity data with one or more leaf nodes in an interest taxonomy. The generated user-interest vector is further utilized for recommending targeted content to the user.

Abstract: The present disclosure discloses methods and systems for identifying a target profile of a source user on a target social network, based on a corresponding source profile at a source social network. The method includes extracting one or more matching profiles from the target social network, based on one or more static profile features of the source profile, determining one or more dynamic profile features of the source profile and each matching profile, based on real-time user activities on the source and target social networks, and identifying the target profile from the one or more matching profiles, based on a comparison of the one or more dynamic profile features of the source profile with corresponding one or more features of the one or more matching profiles.

Abstract: A method and non-transitory computer readable medium for generating patient profiles via a social media service are disclosed. For example, the method receives data from the social media service, extracts one or more attributes from the data from the social media service, classifies the one or more attributes to one or more of a plurality of predefined profile attributes, generates a patient profile based on the one or more attributes that are classified, determines a medical action to be executed based on the patient profile and transmits the medical action to be executed to a health administration server.

Abstract: A method and a system for generating a search query to extract one or more relevant messages from a plurality of messages shared over a computer network. The method includes extracting a plurality of keywords and information pertaining to a plurality of customers from the plurality of messages. Further, the method identifies a set of influential customers from the plurality of customers based on a first score and a second score. The method further includes extracting a set of influential keywords from a first set of messages based on a first number of occurrences of the plurality of keywords in the plurality of messages within a pre-defined time interval. The method further includes generating the search query that includes at least the set of influential customers and the set of influential keywords.

Abstract: What is disclosed is a customer relationship management system to help customer care agents prioritize a response to an incoming message. Historical conversations between customers and agents are retrieved. Each conversation has associated features and an assigned priority. Features are categorized into a plurality of categories. A priority is assigned to each category based on the features and the cumulative priority of all conversations in each category. Thereafter, an incoming message is received from a customer's computing device. Features are extracted from the incoming message. A determination is then made as to which of the categories this incoming message belongs based on this message's features. A priority is then assigned to the incoming message based on a priority assigned to the category which the incoming message belongs. The priority is then displayed for a customer agent so the agent can prioritize his/her response to that customer's incoming message.

Abstract: What is disclosed is a customer relationship management system to help customer care agents prioritize a response to an incoming message. Historical conversations between customers and agents are retrieved. Each conversation has associated features and an assigned priority. Features are categorized into a plurality of categories. A priority is assigned to each category based on the features and the cumulative priority of all conversations in each category. Thereafter, an incoming message is received from a customer's computing device. Features are extracted from the incoming message. A determination is then made as to which of the categories this incoming message belongs based on this message's features. A priority is then assigned to the incoming message based on a priority assigned to the category which the incoming message belongs. The priority is then displayed for a customer agent so the agent can prioritize his/her response to that customer's incoming message.

Abstract: An apparatus, method and non-transitory computer readable medium for developing a query on a social media service are disclosed. For example, the apparatus includes a processor and a computer readable medium storing a plurality of instructions, which when executed by the processor, cause the processor to perform operations for developing the query on the social media service. The operations include receiving a keyword, providing an option to select a sentiment and an option to include a time frame, finding a plurality of related keywords based on the keyword, the sentiment that is selected and the time frame that is selected using one or more external databases, generating the query using the keyword and all of the plurality of related keywords and the time frame that is selected and applying the query to the social media service.

Abstract: The disclosed embodiments illustrate methods and systems for creating event-triggered marketing campaigns. The method includes determining one or more events by analyzing messages of one or more users on social media platforms. Each event has an associated location and a timeline. Thereafter, one or more first attributes, associated with a set of users, corresponding to each event, are determined from the one or more users. Further, one or more target customers are determined from one or more customers of an organization based on the one or more first attributes and one or more second attributes of the one or more customers. Thereafter, the marketing campaigns are created for the one or more target customers based on the one or more second attributes and a historical data of the one or more target customers. Further, media delivery channels for the marketing campaigns are determined based on the timeline of each event.

Abstract: Methods and systems for categorizing users. A first set of communities and a second set of communities are identified based on a set of keywords and one or more messages posted by at least the users on one or more websites. The first set of communities corresponds to at least one of a product or a service, and second set of communities corresponds to at least one of a competitor-product or a competitor-service. The one or more conversations associated a user in at least one of the first set of communities or the second set of communities are determined. The one or more conversations correspond to exchange of messages at least between the user and a user-representative. The one or more conversations are analyzed to obtained one or more attributes. The users are categorized based on the one or more attributes.

Abstract: A first embodiment of the disclosure relates to a method for responding to a message posted in a social media stream. The method includes monitoring a social media site for at least one message including select subject matter. In response to identifying a message, the method includes collecting a series of exchanges that form a conversational thread including the message. The method includes determining at least one content attribute of the message. The method includes classifying the message using at least one key attribute. The method includes searching a database for a reference message using a combination of the at least one content and key attributes. The method includes determining a previous outcome of a reference thread including the reference message. The method includes using the previous outcome for determining a course of action.

Abstract: Systems and methods of analyzing message data. An embodiment is a method of analyzing message data including a plurality of messages associated with one or more users. The method is performed using a computing system comprising a computer storage medium and a computer processor. The system parses each message of the plurality of messages to identify a plurality of message segments. The system assigns the message segments to the one or more users. The assignment is based at least in part on a determination of whether each message of the plurality of messages is a reply message. The segments of the message are assigned to a reply user if the message is determined to be a reply message. The system applies a statistical model to the assigned message segments, to determine predicted locations for the users. The system outputs the predicted locations for the users.