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CUVIM: Extracting Fresh Information from Social Network

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Web-Age Information Management (WAIM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7923))

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Abstract

Social network preserves the life of users and provides great potential for journalists, sociologists and business analysts. Crawling data from social network is a basic step for social network information analysis and processing. As the network becomes huge and information on the network updates faster than web pages, crawling is more difficult because of the limitations of bandwidth, politeness etiquette and computation power. To extract fresh information from social network efficiently and effectively, this paper presents a novel crawling method of social network. To discover the feature of social network, we gather data from real social network, analyze them and build a model to describe the discipline of users’ behavior. With the modeled behavior, we propose methods to predict users’ behavior. According to the prediction, we schedule our crawler more reasonably and extract more fresh information. Experimental results demonstrate that our strategies could obtain information from SNS efficiently and effectively.

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Author information

Authors and Affiliations

  1. Harbin Institute of Technology, China

    Rui Guo, Hongzhi Wang, Kaiyu Li, Jianzhong Li & Hong Gao

Authors
  1. Rui Guo
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  2. Hongzhi Wang
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  3. Kaiyu Li
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  4. Jianzhong Li
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  5. Hong Gao
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China

    Jianyong Wang

  2. Management Science and Information Systems Department, Rutgers, the State University of New Jersey, 1, Washington Park, 07102, Newark, NJ, USA

    Hui Xiong

  3. Department of Information Engineering, Nagoya University, 464-8601, Nagoya, Japan

    Yoshiharu Ishikawa

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong

    Jianliang Xu

  5. School of Information Science and Engineering, Yanshan University, Qinhuangdao, China

    Junfeng Zhou

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© 2013 Springer-Verlag Berlin Heidelberg

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Guo, R., Wang, H., Li, K., Li, J., Gao, H. (2013). CUVIM: Extracting Fresh Information from Social Network. In: Wang, J., Xiong, H., Ishikawa, Y., Xu, J., Zhou, J. (eds) Web-Age Information Management. WAIM 2013. Lecture Notes in Computer Science, vol 7923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38562-9_36

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  • DOI: https://doi.org/10.1007/978-3-642-38562-9_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38561-2

  • Online ISBN: 978-3-642-38562-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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