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Hot Topic Detection Research of Internet Public Opinion Based on Affinity Propagation Clustering

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Computer, Informatics, Cybernetics and Applications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 107))

Abstract

Internet is becoming a spreading platform for public opinion. It is very important to grasp hotspot of internet public opinion (IPO) in time and understand the trends of them correctly. Aim at such drawbacks of some text clustering algorithm as information massive, curse of dimensionality, longer analysis time, lower analysis efficiency, this chapter introduces affinity propagation algorithm into hot topic detection of IPO, with the center of each clustering representing a topic. Through compared result of experiment affinity propagation clustering and K-Means algorithm, it shows that the efficiency and effectiveness of such the algorithm.

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Acknowledgment

This chapter is supported by the Natural Science Foundation project of ZheJiang provincial (No. Y1110995). And this chapter is also supported the National Natural Science Foundation of China under Grant No. 60903053.

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Authors and Affiliations

  1. College of Computer and Information Engineering, Zhejiang Gongshang University, HangZhou, China

    Hong Liu & Bi Wei Li

Authors
  1. Hong Liu
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  2. Bi Wei Li
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Corresponding author

Correspondence to Hong Liu .

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Editors and Affiliations

  1. Chinese Academy of Engineering, Beijing, China, People's Republic

    Xingui He

  2. Zhejiang Gongshang University, Beijing, China, People's Republic

    Ertian Hua

  3. Zhejiang Gongshang University, Hangzhou, China, People's Republic

    Yun Lin

  4. , School of Automation, Wuhan University of Technology, East District of Wuhan University, Luoshi Road 122, Wuhan, 4300, China, People's Republic

    Xiaozhu Liu

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Liu, H., Li, B.W. (2012). Hot Topic Detection Research of Internet Public Opinion Based on Affinity Propagation Clustering. In: He, X., Hua, E., Lin, Y., Liu, X. (eds) Computer, Informatics, Cybernetics and Applications. Lecture Notes in Electrical Engineering, vol 107. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1839-5_28

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  • DOI: https://doi.org/10.1007/978-94-007-1839-5_28

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1838-8

  • Online ISBN: 978-94-007-1839-5

  • eBook Packages: EngineeringEngineering (R0)

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