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The influence of feedback with different opinions on continued user participation in online newsgroups
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.ORCID iD: 0000-0003-3219-9598
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2013 (English)In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, IEEE Computer Society, 2013, 388-395 p.Conference paper, (Refereed)
Abstract [en]

With the popularity of social media in recent years, it has been a critical topic for social network designer to understand the factors that influence continued user participation in online newsgroups. Our study examines how feedback with different opinions is associated with participants' lifetime in online newsgroups. Firstly, we propose a new method of classifying different opinions among user interaction contents. Generally, we leverage user behavior information in online newsgroups to estimate their opinions and evaluate our classification results based on linguistic features. In addition, we also implement this opinion classification method into our SINCERE system as a real-time service. Based on this opinion classification tool, we use survival analysis to examine how others' feedback with different opinions influence continued participation. In our experiment, we analyze more than 88,770 interactions on the official Occupy LA Facebook page. Our final result shows that not only the feedback with the same opinions as the user, but also the feedback with different opinions can motivate continued user participation in online newsgroup. Furthermore, an interaction of feedback with both the same and different opinions can boost user continued participation to the greatest extent. This finding forms the basis of understanding how to improve online service in social media. Copyright 2013 ACM.

Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 388-395 p.
Keyword [en]
Continued user participation, Online newsgroups, Opinion classification, Social influence, Behavioral research, Classification (of information), Information services, Classification methods, Classification results, Classification tool, Continued participations, Influence of feedback, Newsgroups, User participation, Social networking (online)
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-10892DOI: 10.1145/2492517.2492555Scopus ID: 2-s2.0-84893317677ISBN: 9781450322409 (print)OAI: oai:DiVA.org:bth-10892DiVA: diva2:865143
Conference
2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, 25 August 2013 through 28 August 2013, Niagara Falls, ON
Note

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Available from: 2015-10-27 Created: 2015-10-27 Last updated: 2016-09-06Bibliographically approved

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