InfluenceRank: Trust-Based Influencers Identification Using Social Network Analysis in Q&A Sites
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概要
- 論文の詳細を見る
Question and Answering (Q&A) sites are recently gaining popularity on the Web. People using such sites are like a community-anyone can ask, anyone can answer, and everyone can share, since all of the questions and answers are public and searchable immediately. This mechanism can reduce the time and effort to find the most relevant answer. Unfortunately, the users suffer from answer quality problem due to several reasons including limited knowledge about the question domain, bad intentions (e.g. spam, making fun of others), limited time to prepare good answers, etc. In order to identify the credible users to help people find relevant answer, in this paper, we propose a ranking algorithm, InfluenceRank, which is basis of analyzing relationship in terms of users' activities and their mutual trusts. Our experimental studies show that the proposed algorithm significantly outperforms the baseline algorithms.
著者
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Lee Soojin
Department Of Microbiology Chungnam National University
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Seo Sunghoon
Department Of Computer Science Yonsei University
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Lee Sanghoon
Department Of Biomedical Engineering College Of Medicine Dankook University
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PARK GunWoo
Department of Information System, Korea National Defense University
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