Retrieving rising stars in focused community question-answering

Long T. Le, Chirag Shah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

In Community Question Answering (CQA)‘ forums, there is typically a small fraction of users who provide high-quality posts and earn a very high reputation status from the community. These top contributors are critical to the community since they drive the development of the site and attract traffic from Internet users. Identifying these individuals could be highly valuable, but this is not an easy task. Unlike publication or social networks, most CQA sites lack information regarding peers, friends, or collaborators, which can be an important indicator signaling future success or performance. In this paper, we attempt to perform this analysis by extracting different sets of features to predict future contribution. The experiment covers 376,000 users who remain active in Stack Overflow for at least one year and together contribute more than 21 million posts. One of the highlights of our approach is that we can identify rising stars after short observations. Our approach achieves high accuracy, 85%, when predicting whether a user will become a top contributor after a few weeks of observation. As a slightly different problem in which we could observe a few posts by a user, our method achieves accuracy higher than 90 %. Our approach provides higher accuracy than baselines methods including a popular time series analysis. Furthermore, our methods are robust to different classifier algorithms. Identifying the rising stars early could help CQA administrators gain an overview of the site’s future and ensure that enough incentive and support is given to potential contributors.

Original languageEnglish (US)
Title of host publicationIntelligent Information and Database Systems - 8th Asian Conference, ACIIDS 2016, Proceedings
EditorsTzung-Pei Hong, Ngoc Thanh Nguyen, Bogdan Trawinski, Hamido Fujita
PublisherSpringer Verlag
Pages25-36
Number of pages12
ISBN (Print)9783662493892
DOIs
StatePublished - 2016
Event8th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2016 - Da Nang, Viet Nam
Duration: Mar 14 2016Mar 16 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9622
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2016
Country/TerritoryViet Nam
CityDa Nang
Period3/14/163/16/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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