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Socializing or knowledge sharing?: characterizing social intent in community question answering

Published: 02 November 2009 Publication History

Abstract

Knowledge sharing communities, such as Wikipedia or Yahoo! Answers, add greatly to the wealth of information available on the Web. They represent complex social ecosystems that rely on user paricipation and the quality of users' contributions to prosper. However, quality is harder to achieve when knowledge sharing is facilitated through a high degree of personal interactions. The individuals' objectives may change from knowledge sharing to socializing, with a profound impact on the community and the value it delivers to the broader population of Web users. In this paper we provide new insights into the types of content that is shared through Community Question Answering (CQA) services. We demonstrate an approach that combines in-depth content analysis with social network analysis techniques. We adapted the Undirected Inductive Coding method to analyze samples of user questions and arrive at a comprehensive typology of the user intent. In our analysis we focused on two types of intent, social vs. non-social, and define measures of social engagement to characterize the users' participation and content contributions. Our approach is applicable to a broad class of online communities and can be used to monitor the dynamics of community ecosystems.

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  • (2020)Extracting core answers using the grey wolf optimizer in community question answeringApplied Soft Computing10.1016/j.asoc.2020.10612590(106125)Online publication date: May-2020
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  • (2018)Identifying Informational vs. Conversational Questions on Community Question Answering ArchivesProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159733(216-224)Online publication date: 2-Feb-2018
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cover image ACM Conferences
CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management
November 2009
2162 pages
ISBN:9781605585123
DOI:10.1145/1645953
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 November 2009

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Author Tags

  1. Q&A community
  2. question typology
  3. social scores
  4. user intent

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  • (2020)Extracting core answers using the grey wolf optimizer in community question answeringApplied Soft Computing10.1016/j.asoc.2020.10612590(106125)Online publication date: May-2020
  • (2018)A methodological pilot for gathering data through text-messaging to study question-asking in everyday lifeMobile Media & Communication10.1177/20501579177413336:2(197-214)Online publication date: 22-Jan-2018
  • (2018)Identifying Informational vs. Conversational Questions on Community Question Answering ArchivesProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159733(216-224)Online publication date: 2-Feb-2018
  • (2017)Towards Mathematical AI via a Model of the Content and Process of Mathematical Question and Answer DialoguesIntelligent Computer Mathematics10.1007/978-3-319-62075-6_10(132-146)Online publication date: 28-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)Seven Words You Can't Say on AnswerbagProceedings of the 27th ACM Conference on Hypertext and Social Media10.1145/2914586.2914603(27-36)Online publication date: 10-Jul-2016
  • (2016)Music Information Seeking via Social Q&AProceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries10.1145/2910896.2910914(139-142)Online publication date: 19-Jun-2016
  • (2016)Multidimensional scaling based knowledge provision for new questions in community Question Answering systems2016 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN.2016.7727188(115-122)Online publication date: Jul-2016
  • (2016)Does everybody lie? characterizing answerers in health-related CQA2016 International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT)10.1109/FRUCT.2016.7584763(1-6)Online publication date: 4-Sep-2016
  • (2015)Collective Sensemaking in Online Health ForumsProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems10.1145/2702123.2702566(3217-3226)Online publication date: 18-Apr-2015
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