Discovering regular and consistent behavioral patterns in topical tweeting

The study of user activity and information in microblogging sites like Twitter has gained momentum to provide real insights about user influence, predicting their actions and information flow optimization. In this paper we present a wavelet-based clustering mechanism that can group users according to their temporal activity profiles. Our study establishes that users of different professionals with different objectives can be effectively segregated using temporal profile clustering.