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International Conference on Advanced Data Mining and Applications

ADMA 2009: Advanced Data Mining and Applications pp 140–151Cite as

Chinese Blog Clustering by Hidden Sentiment Factors

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5678))

Abstract

In the Web age, blogs have become the major platform for people to express their opinions and sentiments. The traditional blog clustering methods usually group blogs by keywords, stories or timelines, which do not consider opinions and emotions expressed in the articles. In this paper, a novel method based on Probabilistic Latent Semantic Analysis (PLSA) is presented to model the hidden emotion factors and an emotion-oriented clustering approach is proposed according to the sentiment similarities between Chinese blogs. Extensive experiments were conducted on real world blog datasets with different topics and the results show that our approach can cluster Chinese blogs into sentiment coherent groups to allow for better organization and easy navigation.

This work is supported by National Natural Science Foundation of China (No. 60573090, 60703068, 60673139) and the National High-Tech Development Program (2008AA01Z146).

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Author information

Authors and Affiliations

  1. Key Laboratory of Medical Image Computing, Northeastern University, Ministry of Education, USA

    Daling Wang & Ge Yu

  2. College of Information Science and Engineering, Northeastern University, 110004, Shenyang, Liaoning

    Shi Feng, Daling Wang, Ge Yu, Chao Yang & Nan Yang

Authors
  1. Shi Feng
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  2. Daling Wang
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  3. Ge Yu
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  4. Chao Yang
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  5. Nan Yang
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Editor information

Editors and Affiliations

  1. Knowledge Science & Engineering Institute, School of Education Technology, Beijing Normal University, Xinjiekouwai Ave. 19, 100875, Beijing, China

    Ronghuai Huang

  2. The Hong Kong University of Science and Technology, Clear Water Bay,, Hong Kong, Hong Kong

    Qiang Yang

  3. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    Jian Pei

  4. Faculty of Economics, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    João Gama

  5. School of Information, Zhongguancum, Renmin University, 100872, Beijing, China

    Xiaofeng Meng

  6. School of Information Technology and Electrical Engineering, The University of Queensland, 4072, St. Lucia, Queensland, Australia

    Xue Li

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Feng, S., Wang, D., Yu, G., Yang, C., Yang, N. (2009). Chinese Blog Clustering by Hidden Sentiment Factors. In: Huang, R., Yang, Q., Pei, J., Gama, J., Meng, X., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2009. Lecture Notes in Computer Science(), vol 5678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03348-3_16

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  • DOI: https://doi.org/10.1007/978-3-642-03348-3_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03347-6

  • Online ISBN: 978-3-642-03348-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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