Modelling question selection behaviour in online communities

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Abstract

Value of online Question Answering (QandA) communities is driven by the question-answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the effcient operation of such communities. In this paper, we aim to identify the parameters that cor- relate with such behaviours. We train different models and construct effective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.

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Details

Publication date18 May 2015
Publication titleWWW'15 Companion - Proceedings of the 24th International Conference on World Wide Web
Place of PublicationNew York, NY (US)
PublisherACM
Pages357-358
Number of pages2
ISBN (Print)978-1-4503-3473-0
Original languageEnglish
Event24th International Conference on World Wide Web - Florence, Italy

Conference

Conference24th International Conference on World Wide Web
Abbreviated titleWWW 2015
CountryItaly
CityFlorence
Period18/05/1522/05/15

Bibliographic note

Funding: EC-FP7 project DecarboNet (grant number 265454).

    Keywords

  • online communities, social media, social QandA platforms, user behaviour

DOI

Employable Graduates; Exploitable Research

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