System and method for classification of microblog posts based on identification of topics

A system for assigning a topic to a collection of microblog posts, the system comprising:

• a processing device;
• and
• a computer-readable memory containing programming instructions that, when executed by the processing device, cause the processing device to:
• by an acquisition module, receive from at least one messaging service server, a plurality of posts, wherein:
• each of the plurality of posts comprise post content, and
• one or more of the posts comprise one or more links with an address to an external document;
• by the acquisition module, cause a communications hardware component to initiate a communication via a communications network that accesses the external document at an external server that is associated with the address and fetches external content associated with the document;
• by the generation module:
• analyze the post content included in each post to identify at least one label for that post,
• for each post that includes a link, analyze external content corresponding to the external document associated with that link to identify a topic, and
• use a topic modeling technique to generate a trained topic model, wherein the trained topic model comprises, for each identified label, a plurality of topics and a plurality of words associated with each of the plurality of topics;
• and
• by the generation module, save the trained topic model to a computer-readable memory device
• wherein, the topic modeling technique comprises a User-Labeled Linked Hierarchical Dirichlet Process (L2-HDP) technique, that utilizes a user's interest variable vector to generate the trained topic model, wherein the user's interest variable vector is indicative of a topic composition of the set of documents associated with a user.