The Open UniversitySkip to content
 

Modelling and analysis of user behaviour in online communities

Angeletou, Sofia; Rowe, Matthew and Alani, Harith (2011). Modelling and analysis of user behaviour in online communities. In: 10th International Semantic Web Conference (ISWC 2011), 23 - 27 Oct 2010, Bonn, Germany, pp. 35–50.

Full text available as:
[img]
Preview
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1039Kb)
URL: http://iswc2011.semanticweb.org/fileadmin/iswc/Pap...
DOI (Digital Object Identifier) Link: http://doi.org/10.1007/978-3-642-25073-6_3
Google Scholar: Look up in Google Scholar

Abstract

Understanding and forecasting the health of an online community is of great value to its owners and managers who have vested interests in its longevity and success. Nevertheless, the association between community evolution and the behavioural patterns and trends of its members is not clearly understood, which hinders our ability of making accurate predictions of whether a community is flourishing or diminishing. In this paper we use statistical analysis, combined with a semantic model and rules for representing and computing behaviour in online communities. We apply this model on a number of forum communities from Boards.ie to categorise behaviour of community members over time, and report on how different behaviour compositions correlate with positive and negative community growth in these forums.

Item Type: Conference Item
Copyright Holders: 2011 The Authors
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Centre for Policing Research and Learning (CPRL)
Related URLs:
Item ID: 29581
Depositing User: Kay Dave
Date Deposited: 28 Sep 2011 08:24
Last Modified: 05 Oct 2016 00:18
URI: http://oro.open.ac.uk/id/eprint/29581
Share this page:

Altmetrics

Scopus Citations

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk