Early Online Identification of Attention Gathering Items In Social Media

Activity in social media such as blogs, micro-blogs, social networks, etc is manifested via interaction that involves text, images, links and other information items. Naturally, some items attract more attention than others, expressed with large volumes of linking, commenting or tagging activity, to name a few examples. Moreover, high attention can be indicative of emerging events, breaking news or generally indicate information items of interest to a vast set of people. The numbers associated with digital social activity are astonishing: in excess of millions of blog posts, tweets and forums updates per day, millions of tags in photos, news articles or blogs. Being able to identify information items that gather much attention in such a real time information collective is a challenging task. In this paper, we consider the problem of early online identification of items that gather a lot of attention in social media. We model social media activity using ISIS, a stochastic model for Int...

• Type: Conference
• Year: 2010
• Where: WSDM
• Authors: Michael Mathioudakis, Nick Koudas, Peter Marbach
• Keywords: Attention Gathering Items, Data Mining, Digital Social Activity, Social Media Activity, WSDM 2010