Blog Classification Using Tags: An Empirical Study

  • Aixin Sun
  • Maggy Anastasia Suryanto
  • Ying Liu
Conference paper

DOI: 10.1007/978-3-540-77094-7_40

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4822)
Cite this paper as:
Sun A., Suryanto M.A., Liu Y. (2007) Blog Classification Using Tags: An Empirical Study. In: Goh D.HL., Cao T.H., Sølvberg I.T., Rasmussen E. (eds) Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers. ICADL 2007. Lecture Notes in Computer Science, vol 4822. Springer, Berlin, Heidelberg

Abstract

With an exponential growth of Weblogs (or blogs), many blog directories have appeared to help users to locate topical blogs. As tags are commonly used to describe blogs, we study the effectiveness of tags in blog classification. Compared with titles and descriptions, our experiments, using 24,247 blogs, showed that tags could lead to better classification accuracy. It is interesting to observe that more tags did not necessarily lead to better classification accuracy. To better describe blogs, we have also proposed a tag expansion algorithm that assigns a blog more tags that are often co-occur with those already associated with the blog. Our experiments showed that tag expansion helped to improve the recall of blog classification with the price of precision degradation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Aixin Sun
    • 1
  • Maggy Anastasia Suryanto
    • 1
  • Ying Liu
    • 2
  1. 1.Nanyang Technological UniversitySingapore
  2. 2.Hong Kong Polytechnic University, Hong KongChina

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