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What Makes a High-Quality User-Generated Answer?

Published: 01 January 2011 Publication History

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.

Cited By

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  • (2024)Predicting answer acceptability for question-answering systemInternational Journal on Digital Libraries10.1007/s00799-023-00357-225:4(555-568)Online publication date: 1-Dec-2024
  • (2023)Understanding user‐generated questions in social Q&AJournal of the Association for Information Science and Technology10.1002/asi.2477074:8(990-1009)Online publication date: 1-Jul-2023
  • (2022)Asking for help in community question-answeringProceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries10.1145/3529372.3533287(1-5)Online publication date: 20-Jun-2022
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Information & Contributors

Information

Published In

cover image IEEE Internet Computing
IEEE Internet Computing  Volume 15, Issue 1
January 2011
91 pages

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 January 2011

Author Tags

  1. Internet
  2. quality framework
  3. question answering
  4. question answering, quality framework, Internet

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Cited By

View all
  • (2024)Predicting answer acceptability for question-answering systemInternational Journal on Digital Libraries10.1007/s00799-023-00357-225:4(555-568)Online publication date: 1-Dec-2024
  • (2023)Understanding user‐generated questions in social Q&AJournal of the Association for Information Science and Technology10.1002/asi.2477074:8(990-1009)Online publication date: 1-Jul-2023
  • (2022)Asking for help in community question-answeringProceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries10.1145/3529372.3533287(1-5)Online publication date: 20-Jun-2022
  • (2019)Finding Informative Comments for Video ViewingSN Computer Science10.1007/s42979-019-0048-21:1Online publication date: 21-Nov-2019
  • (2018)Web Forum Retrieval and Text AnalyticsFoundations and Trends in Information Retrieval10.1561/150000006212:1(1-163)Online publication date: 3-Jan-2018
  • (2017)Asking for more than an answerJournal of Information Science10.1177/016555151664553043:3(424-435)Online publication date: 1-Jun-2017
  • (2016)A Comprehensive Survey and Classification of Approaches for Community Question AnsweringACM Transactions on the Web10.1145/293468710:3(1-63)Online publication date: 16-Aug-2016
  • (2016)A novel framework for social web forums' thread ranking based on semantics and post quality featuresThe Journal of Supercomputing10.1007/s11227-016-1839-z72:11(4276-4295)Online publication date: 1-Nov-2016
  • (2015)Answer Quality Characteristics and Prediction on an Academic Q&A SiteProceedings of the 24th International Conference on World Wide Web10.1145/2740908.2742129(1453-1458)Online publication date: 18-May-2015
  • (2015)Lessons learned from the design of situated learning environments to support collaborative knowledge constructionComputers & Education10.1016/j.compedu.2015.03.01987:C(70-82)Online publication date: 1-Sep-2015
  • Show More Cited By

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