Title :
Discovering regular and consistent behavioral patterns in topical tweeting
Author :
Dey, Lipika ; Gaonkar, Bilwaj
Abstract :
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.
Keywords :
behavioural sciences computing; data mining; optimisation; pattern clustering; social networking (online); wavelet transforms; Twitter; consistent behavioral pattern discovery; information flow optimization; microblogging site; regular behavioral pattern discovery; temporal activity profile clustering; topical tweeting; user activity; wavelet-based clustering mechanism; Communities; Games; Media; Organizations; Twitter;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4
