Title
Weibo clustering: A new approach utilizing users' reposting data in social networking services.
Abstract
As one of the most popular Social Networking Services (SNS) in China, Weibo is generating massive contents, relations and users' behavior data. Many challenges exist in how to analyze Weibo data. Most works focus on Weibo clustering and topic classification based on analyzing the text contents only. However, the traditional approaches do not work well because most messages on Weibo are very short Chinese sentences. This paper aims to propose a new approach to cluster the Weibo data by analyzing the users' reposting behavior data besides the text contents. To verify the proposed approach, a data set of users' real behaviors from the actual SNS platform is utilized. Experimental results show that the proposed method works better than previous works which depend on the text analysis only.
Year
DOI
Venue
2014
10.2298/CSIS130927070Z
COMPUTER SCIENCE AND INFORMATION SYSTEMS
Keywords
Field
DocType
behavior data,clustering,data mining,microblog,Weibo,Social Networking Services
Data mining,World Wide Web,Social media,Social network,Computer science,Microblogging,Cluster analysis
Journal
Volume
Issue
ISSN
11
SP3
1820-0214
Citations 
PageRank 
References 
2
0.36
17
Authors
4
Name
Order
Citations
PageRank
Guangzhi Zhang122.05
Yunchuan Sun253454.06
Mengling Xu320.36
Rongfang Bie454768.23