Online spam-blog detection through blog search

Linhong Zhu*, Aixin Sun, Koon Kau CHOI

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

In this work, we propose a novel post-indexing spam-blog (or splog) detection method, which capitalizes on the results returned by blog search engines. More specifically, we analyze the search results of a sequence of temporallyordered queries returned by a blog search engine, and build and maintain blog profiles for those blogs whose posts frequently appear in the top-ranked search results. With the blog profiles, 4 splog scoring functions were evaluated using real data collected from a popular blog search engine. Our experiments show that the proposed method could effectively detect splogs with a high accuracy.

Original languageEnglish
Title of host publicationProceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
Pages1347-1348
Number of pages2
DOIs
Publication statusPublished - 2008
Event17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States
Duration: 26 Oct 200830 Oct 2008

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference17th ACM Conference on Information and Knowledge Management, CIKM'08
Country/TerritoryUnited States
CityNapa Valley, CA
Period26/10/0830/10/08

Scopus Subject Areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

User-Defined Keywords

  • Experimentation

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