Subject-based extraction of a latent blog community

Seok Ho Yoon, Jung Hwan Shin, Sang Wook Kim, Sunju Park, Jae Bum Lee

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In the blogosphere, there exist posts relevant to a particular subject and blogs that show interest in the subject. In this paper, we define a set of such posts and blogs as a blog community and propose a method for extracting the blog community associated with a particular subject. The proposed method is based on the idea that the blogs who have performed actions (e.g., read, comment, trackback, scrap) to the posts of a particular subject are the ones with interest in the subject, and that the posts that have received actions from such blogs are the ones that contain the subject. The proposed method starts with a small number of manually-selected seed posts containing the subject. Then, the method selects the blogs that have performed actions to the seed posts over some threshold and the posts that have received actions over some threshold. Repeating these two steps gradually expands the blog community. This paper presents various techniques to improve the accuracy of the proposed method. The experimental results show that the proposed method exhibits a higher level of accuracy than the methods proposed in prior research. This paper also discusses business applications of the extracted community, such as target marketing, market monitoring, improving search results, finding power bloggers, and revitalization of the blogosphere.

Original languageEnglish
Pages (from-to)215-229
Number of pages15
JournalInformation sciences
Volume184
Issue number1
DOIs
Publication statusPublished - 2012 Feb 1

Bibliographical note

Funding Information:
This work was supported by NHN Corp. Any opinions, findings, and conclusions or recommendations expressed in this material are the authors and do not necessarily reflect those of the sponsor. This work was also supported by the Mid-Career Researcher Program through the NRF (National Research Foundation) Grant funded by the MEST (Ministry of Education, Science, and Technology) (Grant No. 2008-0061006 ) and the MKE (The Ministry of Knowledge Economy), Korea, under the ‘National HRD Support Program for Convergence Information Technology’ supervised by the NIPA (National IT Industry Promotion Agency) ( NIPA-2011-C6150-1101-0001 ).

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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