Weibo Clustering: A New Approach Utilizing Users’ Reposting Data in Social Networking Services

Guangzhi Zhang1, Yunchuan Sun2, Mengling Xu1 and Rongfang Bie1

  1. College of Information Science and Technology, Beijing Normal University
    100875 Beijing, China
    {zgz, xml}@mail.bnu.edu.cn, rfbie@bnu.edu.cn
  2. Business School, Beijing Normal University
    100875 Beijing, China
    yunch@bnu.edu.cn

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.

Key words

behavior data, clustering, data mining, microblog, Weibo, Social Networking Services

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS130927070Z

Publication information

Volume 11, Issue 3 (August 2014)
Special Issue on Mobile Collaboration Technologies and Internet Services
Year of Publication: 2014
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Zhang, G., Sun, Y., Xu, M., Bie, R.: Weibo Clustering: A New Approach Utilizing Users’ Reposting Data in Social Networking Services. Computer Science and Information Systems, Vol. 11, No. 3, 1157–1172. (2014)