Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Chen, Lin & Nayak, Richi (2012) Leveraging the network information for evaluating answer quality in a collaborative question answering portal. Social Network Analysis and Mining, 2(3), pp. 197-215.

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    Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

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    ID Code: 48198
    Item Type: Journal Article
    Keywords: social network analysis, collaborative question answering portal, non-content method, content method
    DOI: 10.1007/s13278-011-0046-4
    ISSN: 1869-5450
    Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DATA FORMAT (080400)
    Divisions: Past > Schools > Computer Science
    Past > QUT Faculties & Divisions > Faculty of Science and Technology
    Copyright Owner: Copyright 2012 Please consult the authors.
    Copyright Statement: The original publication is available at SpringerLink http://www.springerlink.com
    Deposited On: 24 Jan 2012 10:18
    Last Modified: 27 Feb 2013 06:59

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