Content Mining of Microblogs

Abstract

Emergence of Web 2.0, internet users can share their contents with other users using social networks. In this paper microbloggers' contents are evaluated with respect to how they reflect their categories. Migrobloggers' category information, which is one of the four categories that are economy sport, entertainment or technology, is taken from wefollow.com application. 2105 RSS news feeds, whose category labels are same with microbloggers' contributions, are used as training data for classification. In this study two types of users' contributions are taken as test data. These users are normal microbloggers and bots. Classification results show that bots provide more categorical content than normal users.