Abstract: In social data networks, it is difficult for a computing system to automatically identify age attributes associated with user accounts because of incorrect, incomplete or non-existent data associated with the user account profile. Therefore, a computing system is provided that retrieves user account data and related text data, and that uses classification to identify age data. Label propagation computations based on the connections in the social data network are used to infer the age information of many user accounts at the same time.

Abstract: In social data networks, it is difficult for a computing system to automatically identify gender attributes associated with user accounts because of incorrect, incomplete or non-existent data associated with the user account profile. Therefore, a computing system is provided that retrieves user account data and related text data, and that uses classification to identify gender data. Label propagation computations based on the connections in the social data network are used to infer the gender information of many user accounts at the same time.

Abstract: In social data networks, it is difficult for a computing system to automatically identify demographic attributes associated with user accounts because of incorrect, incomplete or non-existent data associated with the user account profile. Therefore, a computing system is provided that retrieves user account data and related text data, and that uses Deep Learning computations to infer demographic attributes about a given user based on the text data that they generate. The text is processed, and then inputted into a bi-gram neural network to generate an initial feature vector. This initial feature vector is inputted into a Deep Learning neural network in order to generate a secondary feature vector. The secondary feature vector is inputted into a forward neural network to generate one or more values indicating a specific demographic attribute associated with the given user account.

Abstract: Data infrastructure systems and methods are provided for updating a continuously evolving social network. The social network is representable by a social network graph. A client application and graph data are retrieved from a database that stores the social network graph, in order to determine current activity in the social network. The current activity is used to determine one or more priority nodes in the social network graph to be updated. Social network updates are obtained for each of the one or more priority nodes. The one or more priority nodes in the social network graph are updated using the social network updates.

Abstract: A system and method performed by a server for determining at least one user account that is influential for a topic: obtaining the topic; determining a plurality of user accounts within a social data network that are related to the topic; representing each of the user accounts as a node in a connected graph and determining an existence of a relationship between each of the user accounts; computing a topic network graph using each of the user accounts as nodes and the corresponding relationships as edges between each of the nodes; ranking the user accounts within the topic network graph to filter outlier nodes within the topic network graph; identifying at least two distinct communities amongst the user accounts within the filtered topic network graph, each community associated with a subset of the user accounts; identifying attributes associated with each community; outputting each community associated with the corresponding attributes.

Abstract: There is provided methods and systems for analyzing data from a plurality of users within a social networking platform, comprising: receiving a query for a topic associated with the social networking platform; determining a set of users having at least one social networking behavior on the social networking platform related to the topic; selecting, for each user from the set of users, a pre-defined number of posts and associating each of the pre-defined number of posts with the respective user; segmenting the selected posts for each user to determine a likelihood of each of the selected posts among the set of users; and, clustering the selected posts for each user to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters, each cluster comprising representative topics indicating frequently used topics within the cluster for the pre-defined number of posts between the set of users.

Abstract: A system and a method are provided for continuously analysing and procuring advertisements. Social data is obtained and is used to identify one or more relationships. The operations further include: modifying or determining a target set based on the one or more relationships, the target set comprising a combination of inputs and a target audience, the inputs comprising a search algorithm for identifying the target audience; presenting the target set when a proposed advertising campaign is detected; procuring the proposed advertising campaign using the target audience to generate a procured advertisement; obtaining feedback about the procured advertisement; and further modifying the target set based on the feedback.

Abstract: System and methods performed by a server for determining a target group of users in a social data network, including: obtaining identities of friends from an initial group of users, where a user in the group follows one or more of the friends; determining N number friends that are most frequently occurring amongst the identities of friends from the initial group; for each of the N number friends, obtaining identities of followers following a given one of the N friends; filtering out one or more followers from the identities of the followers that follow less than X number of the N number of friends, where X?N; and including remaining ones of the identities of the followers in the target group of users

Abstract: System and methods performed by a server for determining weighted influence in social networks, including: determining posts related to the topic; characterizing each post as one or more of: a reply post, a mention post, and a re-posting; generating a group of user accounts comprising any user account that authored a posting to which is replied, being mentioned in the mention post, that posted content being re-posted, and/or that authored one or more posts that are related to the topic; representing each of the user accounts as a node in the group in a connected graph and establishing an edge between one or more pair of nodes when there is a follower-followee relationship between the nodes; and for each edge between nodes, determining a weighting that is a function of one or more of: a number of mention posts, a number of reply posts, and a number of re-posts.

Abstract: There is provided methods and systems for analyzing data from a plurality of users within a social networking platform, comprising: receiving a query for a topic associated with the social networking platform; determining a set of users having at least one social networking behaviour on the social networking platform related to the topic; selecting, for each user from the set of users, a pre-defined number of posts and associating each of the pre-defined number of posts with the respective user; segmenting the selected posts for each user to determine a likelihood of each of the selected posts among the set of users; and, clustering the selected posts for each user to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters, each cluster comprising representative topics indicating frequently used topics within the cluster for the pre-defined number of posts between the set of users.

Abstract: System and methods performed by a server for determining weighted influence in social networks, including: determining posts related to the topic; characterizing each post as one or more of: a reply post, a mention post, and a re-posting; generating a group of user accounts comprising any user account that authored a posting to which is replied, being mentioned in the mention post, that posted content being re-posted, and/or that authored one or more posts that are related to the topic; representing each of the user accounts as a node in the group in a connected graph and establishing an edge between one or more pair of nodes when there is a follower-followee relationship between the nodes; and for each edge between nodes, determining a weighting that is a function of one or more of: a number of mention posts, a number of reply posts, and a number of re-posts.

Abstract: A system and method performed by a server for determining at least one user account that is influential for a topic: obtaining the topic; determining a plurality of user accounts within a social data network that are related to the topic; representing each of the user accounts as a node in a connected graph and determining an existence of a relationship between each of the user accounts; computing a topic network graph using each of the user accounts as nodes and the corresponding relationships as edges between each of the nodes; ranking the user accounts within the topic network graph to filter outlier nodes within the topic network graph; identifying at least two distinct communities amongst the user accounts within the filtered topic network graph, each community associated with a subset of the user accounts; identifying attributes associated with each community; outputting each community associated with the corresponding attributes.

Abstract: A method performed by a computing system is provided for searching for text sources including temporally-ordered data objects based on at least influence of an author. Users associated with a topic are identified, including authors. The users are modeled as a node and the method includes computing a topic network graph using the users as nodes and their relationships as edges. Users are ranked within the topic network graph. A search query based on a term and a time interval, including the topic, is obtained. Data objects based on the search query are identified. The method further includes: generating a popularity curve based on the frequency of data objects; identifying popular data objects based on the popularity curve; identifying an author of each of the popular data objects; and ranking the popular data objects according to a respective ranking of a respective author of each of the popular data objects.

Abstract: A system and method performed by a server for determining at least one user account that is influential for a topic: obtaining the topic; determining a plurality of user accounts within a social data network that are related to the topic; representing each of the user accounts as a node in a connected graph and determining an existence of a relationship between each of the user accounts; computing a topic network graph using each of the user accounts as nodes and the corresponding relationships as edges between each of the nodes; ranking the user accounts within the topic network graph to filter outlier nodes within the topic network graph; identifying at least two distinct communities amongst the user accounts within the filtered topic network graph, each community associated with a subset of the user accounts; identifying attributes associated with each community; outputting each community associated with the corresponding attributes.

Abstract: A system and method are provided for obtaining and analysing social data. The obtained social data and the determined relationships can be used to compose new social data and determine transmission parameters of the new social data. A method performed by a computing device or server system includes obtaining social data from one or more data streams, filtering the social data to obtain filtered social data, analysing the filtered social data to determine one or more relationships, and outputting the filtered social data and the one or more relationships in association with each other.