9. A non-transitory computer readable medium comprising computer executable instructions, for when executed by one or more processors are configured for analyzing data from a plurality of users within a social data network, said computer executable instructions configured for: receiving, via a communication device, a query for a topic associated with the social data network; responsive to the query, accessing a data store that stores the data from the plurality of users to determine a set of users in the social data network having at least one social networking behaviour on the social data network related to the queried topic, and determining the set of users further comprises segmenting the set of users from the plurality of users in accordance with at least one common attribute of the social networking behaviour related to the queried topic; for each user from the set of users, applying text processing to posts for each user to extract a list of topic words and associating each of the topic words with the respective user, the posts obtained by accessing the data store; for each user, segmenting each of the topic words into letter segments and computing a statistical likelihood value of each of the letter segments for the respective user; using the statistical likelihood values of each of the letter segments, clustering the topic words to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters; labeling each cluster with one or more highest ranked topic words within the respective cluster used by users mapped to the respective cluster; and outputting the one or more highest ranked topic words mapped to each cluster via the communication device.
9. A non-transitory computer readable medium comprising computer executable instructions, for when executed by one or more processors are configured for analyzing data from a plurality of users within a social data network, said computer executable instructions configured for: receiving, via a communication device, a query for a topic associated with the social data network; responsive to the query, accessing a data store that stores the data from the plurality of users to determine a set of users in the social data network having at least one social networking behaviour on the social data network related to the queried topic, and determining the set of users further comprises segmenting the set of users from the plurality of users in accordance with at least one common attribute of the social networking behaviour related to the queried topic; for each user from the set of users, applying text processing to posts for each user to extract a list of topic words and associating each of the topic words with the respective user, the posts obtained by accessing the data store; for each user, segmenting each of the topic words into letter segments and computing a statistical likelihood value of each of the letter segments for the respective user; using the statistical likelihood values of each of the letter segments, clustering the topic words to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters; labeling each cluster with one or more highest ranked topic words within the respective cluster used by users mapped to the respective cluster; and outputting the one or more highest ranked topic words mapped to each cluster via the communication device. 10. The non-transitory computer readable medium of claim 9 , wherein said at least one social networking behaviour comprises at least one of: a tweet, a post, a comment associated with the queried topic in the social data networking, and being a follower of the queried topic.