DocumentCode
595469
Title
Discovering regular and consistent behavioral patterns in topical tweeting
Author
Dey, Lipika ; Gaonkar, Bilwaj
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
3464
Lastpage
3467
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location
Tsukuba
ISSN
1051-4651
Print_ISBN
978-1-4673-2216-4
Type
conf
Filename
6460910
Link To Document