Application of Association Rule Mining Theory in Sina WeiboReport as inadecuate




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A user profile contains information about a user.A substantial effort has been made so as to understand users’ behavior throughanalyzing their profile data. Online social networks provide an enormous amountof such information for researchers. Sina Weibo, a Twitter-like microbloggingplatform, has achieved a great success in China although studies on it arestill in an initial state. This paper aims to explore the relationships amongdifferent profile attributes in Sina Weibo. We use the techniques ofassociation rule mining to identify the dependency among the attributes and wefound that if a user’s posts are welcomed, he or she is more likely to have alarge number of followers. Our results demonstrate how the relationships amongthe profile attributes are affected by a user’s verified type. We also put someefforts on data transformationand analyze the influence of the statistical properties of the datadistribution on data discretization.

KEYWORDS

Association Rules; User Profiles; Sina Weibo; Social Network

Cite this paper

Cui, X. , Shi, H. and Yi, X. 2014 Application of Association Rule Mining Theory in Sina Weibo. Journal of Computer and Communications, 2, 19-26. doi: 10.4236-jcc.2014.21004.





Author: Xiao Cui, Hao Shi, Xun Yi

Source: http://www.scirp.org/



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