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Acquiring the Gist of Social Network Service Threads via Comparison with Wikipedia

Acquiring the Gist of Social Network Service Threads via Comparison with Wikipedia

Akiyo Nadamoto, Eiji Aramaki, Takeshi Abekawa, Yohei Murakami
Copyright: © 2011 |Volume: 7 |Issue: 2 |Pages: 12
ISSN: 1548-0631|EISSN: 1548-064X|EISBN13: 9781613505861|DOI: 10.4018/jbdcn.2011040102
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MLA

Nadamoto, Akiyo, et al. "Acquiring the Gist of Social Network Service Threads via Comparison with Wikipedia." IJBDCN vol.7, no.2 2011: pp.17-28. http://doi.org/10.4018/jbdcn.2011040102

APA

Nadamoto, A., Aramaki, E., Abekawa, T., & Murakami, Y. (2011). Acquiring the Gist of Social Network Service Threads via Comparison with Wikipedia. International Journal of Business Data Communications and Networking (IJBDCN), 7(2), 17-28. http://doi.org/10.4018/jbdcn.2011040102

Chicago

Nadamoto, Akiyo, et al. "Acquiring the Gist of Social Network Service Threads via Comparison with Wikipedia," International Journal of Business Data Communications and Networking (IJBDCN) 7, no.2: 17-28. http://doi.org/10.4018/jbdcn.2011040102

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Abstract

Internet-based social network services (SNSs) have grown increasingly popular and are producing a great amount of content. Multiple users freely post their comments in SNS threads, and extracting the gist of these comments can be difficult due to their complicated dialog. In this paper, the authors propose a system that explores this concept of the gist of an SNS thread by comparing it with Wikipedia. The granularity of information in an SNS thread differs from that in Wikipedia articles, which implies that the information in a thread may be related to different articles on Wikipedia. The authors extract target articles on Wikipedia based on its link graph. When an SNS thread is compared with Wikipedia, the focus is on the table of contents (TOC) of the relevant Wikipedia articles. The system uses a proposed coverage degree to compare the comments in a thread with the information in the TOC. If the coverage degree is higher, the Wikipedia paragraph becomes the gist of the thread.

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