Determining the strength of the propensities of a blog network

Seok Ho Yoon, Sang Wook Kim, Sunju Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A blog network, composed of blogs and their relations, may exhibit two different propensities characterized by the purpose of use: an information-oriented propensity and a friendship-oriented propensity. Both propensities coexist in a blog network, and the degree of these propensities may play an important role in business and policy decisions of blog-related business. In this paper, we propose an automated method for determining the propensity values of a blog network. First, classification is used to judge the propensity values of the relation between two blogs. Then, by adding up the propensity values of all the relations in the network, one determines the propensity values of the whole network. Through extensive experiments using a large volume of real-world blog data, we demonstrate our method achieves a high level of accuracy in determining the propensity values of a relation. The results also suggest the applicability of our approach for determining the propensity values of a network.

Original languageEnglish
Title of host publication2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
Pages140-145
Number of pages6
DOIs
Publication statusPublished - 2009 Jul 20
Event2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Nashville, TN, United States
Duration: 2009 Mar 302009 Apr 2

Publication series

Name2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings

Other

Other2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009
CountryUnited States
CityNashville, TN
Period09/3/3009/4/2

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Software

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    Yoon, S. H., Kim, S. W., & Park, S. (2009). Determining the strength of the propensities of a blog network. In 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings (pp. 140-145). [4938641] (2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings). https://doi.org/10.1109/CIDM.2009.4938641