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Issue No.01 - January/February (2011 vol.15)
pp: 66-71
Blooma Mohan John , Nanyang Technological University
Alton Yeow-Kuan Chua , Nanyang Technological University
Dion Hoe-Lian Goh , Nanyang Technological University
ABSTRACT
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.
INDEX TERMS
question answering, quality framework, Internet
CITATION
Blooma Mohan John, Alton Yeow-Kuan Chua, Dion Hoe-Lian Goh, "What Makes a High-Quality User-Generated Answer?", IEEE Internet Computing, vol.15, no. 1, pp. 66-71, January/February 2011, doi:10.1109/MIC.2011.23
REFERENCES
1. L.A. Adamic et al., "Knowledge Sharing and Yahoo Answers: Everybody Knows Something," Proc. 17th Int'l Conf. World Wide Web (WWW 08), ACM Press, 2008, pp. 665–674.
2. Y. Liu, J. Bian, and E. Agichtein, "Predicting Information Seeker Satisfaction in Community Question Answering," Proc. 31st Ann. Int'l ACM Sigir Conf. Research and Development in Information Retrieval, ACM Press, 2008, pp. 483–490.
3. J. Jeon et al., "A Framework to Predict the Quality of Answers with Non-textual Features," Proc. 29th Ann. Conf. Special Interest Group in Information Retrieval (Sigir 06), ACM Press, 2006, pp. 228–235.
4. E. Agichtein, Y. Liu, and J. Bian, "Modeling Information Seeker Satisfaction in Community Question Answering," ACM Trans. Knowledge Discovery from Data, vol. 3, no. 2, 2009, pp. 1–27.
5. J. Bian et al., "Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media," Proc. 17th Int'l Conf. World Wide Web (WWW 08), ACM Press, 2008, pp. 467–476.
6. R.S. Taylor, Value-Added Processes in Information Systems, Ablex, 1986.
7. C. Batini and M. Scannapieco, Data Quality: Concepts, Methodologies and Techniques, Springer, 2006.
8. S. Kim and S. Oh, "User's Relevance Criteria for Evaluating Answers in a Social Q&A Site," J. Am Soc. for Information Science and Technology, vol. 60, no. 4, 2009, pp. 716–727.
9. P. Katerattanakul and K. Siau, "Measuring Information Quality of Web Sites: Development of an Instrument," Proc. 20th Int'l Conf. Information Systems, Assoc. for Information Systems, 1999, pp. 279–285.
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