User reputation evaluation using co-occurrence feature and collective intelligence

Jeong Won Cha, Hyun Woo Lee, Yo Sub Han, Laehyun Kim

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

1 Citation (Scopus)

Abstract

It becomes more difficult to find valuable contents in the Web 2.0 environment since lots of inexperienced users provide many unorganized contents. In the previous researches, people has proved that non-text information such as the number of references, the number of supports, and the length of answers is effective to evaluate answers to a question in a online QnA service site. However, these features can be changed easily by users and cannot reflect social activity of users. In this paper, we propose a new method to evaluate user reputation using co-occurrence features between question and answers, and collective intelligence. If we are able to calculate user reputation, then we can estimate the worth of contents that has small number of reference and small number of support. We compute the user reputation using a modified PageRank algorithm. The experiment results show that our proposed method is effective and useful for identifying such contents.

Original languageEnglish
Title of host publicationOnline Communities and Social Computing - Third International Conference, OCSC 2009, Held as Part of HCI International 2009, Proceedings
Pages305-311
Number of pages7
DOIs
Publication statusPublished - 2009 Dec 1
Event3rd International Conference on Online Communities and Social Computing, OCSC 2009. Held as Part of HCI International 2009 - San Diego, CA, United States
Duration: 2009 Jul 192009 Jul 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5621 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Online Communities and Social Computing, OCSC 2009. Held as Part of HCI International 2009
CountryUnited States
CitySan Diego, CA
Period09/7/1909/7/24

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Cha, J. W., Lee, H. W., Han, Y. S., & Kim, L. (2009). User reputation evaluation using co-occurrence feature and collective intelligence. In Online Communities and Social Computing - Third International Conference, OCSC 2009, Held as Part of HCI International 2009, Proceedings (pp. 305-311). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5621 LNCS). https://doi.org/10.1007/978-3-642-02774-1_33