Information Mining from Twitter

Prof. Ebrahim Bagheri, Ryerson University

Thursday November 5th, 2015, 11:00am.
Lassonde Building 3033 – LAS3033

The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance,

the word ‘metal’ when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modelled on Twitter to enable better and more efficient search, retrieval and recommendation of content.


About the Speaker. Ebrahim Bagheri is an Associate Professor and the Director for the Laboratory for Systems, Software and Semantics (LS3) at Ryerson University, and has been active in the areas of the Semantic Web and Software Engineering. He is a Senior Member of IEEE and IBM CAS Fellow. More information can be found at