The microblogging service Twitter has become one of the most popular sources of real time information. Every second, hundreds of URLs are posted on Twitter. Due to the maximum tweet length of 140 characters, these URLs are in most cases a shortened version of the original URLs. In contrast to the original URLS, which usually provide some hints on the destination Web site and the specific page, shortened links do not tell the users what to expect behind them. These links might contain relevant information or news regarding a certain topic of interest, but they might just as well be completely irrelevant, or even lead to a malicious or harmful website. In this paper, we present our work towards identifying credible Twitter users for given topics. We achieve this by characterizing the content of the posted URLs to further relate to the expertise of Twitter users.
['Patrick Siehndel', 'Ricardo Kawase', 'Eelco Herder', 'Thomas Risse']
Identifying topic-related hyperlinks on twitter