Detecting Newsworthy Topics in Twitter
Journal: Ghent University Academic Bibliography (Ghent University)
Year: 2014

The task of the SNOW 2014 Data Challenge is to mine Twitter streams to provide jour-nalists a set of headlines and complementary information that summarize the most news-worthy topics for a number of given time in-tervals. We propose a 4-step approach to solve this. First, a classifier is trained to determine whether a Twitter user is likely to post tweets about newsworthy stories. Second, tweets posted by these users during the time inter-val of interest are clustered into topics. For this clus