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| Ranking Answer Quality of Popular Q&A Community |
Ming Yi( ),Tingting Zhang |
| School of Information Management, Central China Normal University, Wuhan 430079, China |
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Abstract [Objective] This paper proposes a new method to rank the quality of answers from a popular Q&A community in China. [Methods] First, based on the information acceptance model, we established initial quality indicators for the answer’s perceived values. Then, we discretized these indicators with the K-Medoids clustering algorithm. Third, we reduced and weighted the indictors with the help of rough set theory. Finally, we generated the formal rankings with the weighted grey correlation analysis. [Results] We evaluated the proposed method with 2 297 answers for six different types of questions from the Q&A website of “Zhihu”. We found that the answers ranked higher generally included textual message with images. These answers were also more informative than others and involved active members of the Q&A community. [Limitations] The size of our dataset needs to be expanded, and the evaluation method of the proposed model could be optimized. [Conclusions] The proposed method is an effective way to rank the quality of answers from the Q&A community.
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Received: 02 July 2018
Published: 15 August 2019
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