Classifying Trending Topics: A Typology of Conversation Triggers on Twitter
My paper with Damiano Spina, Víctor Fresno and Raquel Martínez entitled “Classifying Trending Topics: A Typology of Conversation Triggers on Twitter” has been accepted for publication and presentation at CIKM 2011, 20th ACM Conference on Information and Knowledge Management to be held in Glasgow, Scotland, from October 24 to 28, 2011.
Twitter summarizes the great deal of messages posted by users in the form of trending topics that reflect the top conversations being discussed at a given moment. These trending topics tend to be connected to current affairs. Different happenings can give rise to the emergence of these trending topics. For instance, a sports event broadcasted on TV, or a viral meme introduced by a community of users. Detecting the type of origin can facilitate information filtering, enhance real-time data processing, and improve user experience. In this paper, we introduce a typology to categorize the triggers that leverage trending topics: news, current events, memes, and commemoratives. We define a set of straightforward language-independent features that rely on the social spread of the trends to discriminate among those types of trending topics. Our method provides an efficient way to immediately and accurately categorize trending topics without need of external data, outperforming a content-based approach.