DocumentCode
2835669
Title
Clustering Users in Micro Blogging Social Networks Using Probabilistic Topic Modeling - A Framework
Author
Dolatabadi, Hossein ; Soon, Lay-Ki ; Shirazi, Mahdi Negahi ; Mohammadi, Mohammad
Author_Institution
Fac. of Comput. & Inf., Multimedia Univ., Selangor, Malaysia
fYear
2012
fDate
18-21 June 2012
Firstpage
113
Lastpage
116
Abstract
Social network is a term used to represent a large group of activities using the web and mobile technologies. The micro blogging social networks provide an appropriate ground for the users to explain themselves and express their ideas as well as interacting with the others. The growth of the social networks´ users creates the necessity of extracting and analyzing the contents of the users´ notes and multimedia products. In this paper, a new methodology is defined to characterize users based on the contents of their posts in micro blogging social networks and also to create clusters of users by means of highlighting the distribution of words representing a topic in the contents of micro blogging social networks.
Keywords
Internet; mobile computing; pattern clustering; probability; social networking (online); text analysis; World Wide Web; microblogging social network; mobile technology; multimedia product; probabilistic topic modeling; user clustering; Algorithm design and analysis; Blogs; Clustering algorithms; Data mining; Media; Twitter; Latent Dirichlet Allocation (LDA); Micro blogging; Social network; Topic modeling algorithm; User clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Science and Its Applications (ICCSA), 2012 12th International Conference on
Conference_Location
Salvador
Print_ISBN
978-1-4673-1691-0
Type
conf
DOI
10.1109/ICCSA.2012.28
Filename
6257619
Link To Document