Discovering Users' Topics of Interest on Twitter: A First Look
[pdf]
In Proceedings of the Workshop on
Analytics for Noisy, Unstructured Text Data (AND), Toronto, Canada, 2010.
Abstract
Twitter, a micro-blogging service, provides users with a framework for
writing brief, often-noisy postings about their lives. These posts
are called &qout;Tweets." In this paper we present early results
on discovering Twitter users' topics of interest by examining the
entities they mention in their Tweets. Our approach leverages a
knowledge base to disambiguate and categorize the entities in the
Tweets. We then develop a "topic profile," which
characterizes users' topics of interest, by discerning which
categories appear frequently and cover the entities. We demonstrate
that even in this early work we are able to successfully discover the
main topics of interest for the users in our study.