What makes a high-quality user-generated answer?
Community-driven question-answering (CQA) services on the Internet let users share content in the form of questions and answers. Usually, questions attract multiple answers of varying quality from other users. A new approach aims to identify high-quality answers from candidate answers to questions t...
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| Main Authors: | , , |
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| 格式: | Article |
| 語言: | English |
| 出版: |
2013
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/100041 http://hdl.handle.net/10220/17794 |
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| 總結: | Community-driven question-answering (CQA) services on the Internet let users share content in the form of questions and answers. Usually, questions attract multiple answers of varying quality from other users. A new approach aims to identify high-quality answers from candidate answers to questions that are semantically similar to the new question. Toward that end, the authors developed and tested a quality framework comprising social, textual, and content-appraisal features of user-generated answers in CQA services. Logistic-regression analysis revealed that content-appraisal features were the strongest predictor of quality. These features include dimensions such as comprehensiveness, truthfulness, and practicality. |
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