The Open UniversitySkip to content

What catches your attention? An empirical study of attention patterns in community forums

Wagner, Claudia; Rowe, Matthew; Strohmaier, Markus and Alani, Harith (2012). What catches your attention? An empirical study of attention patterns in community forums. In: Poster track at Sixth International AAAI Conference on Weblogs and Social Media (ICWSM), 04-08 Jun 2012, Dublin, Ireland.

Full text available as:
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (160kB)
Google Scholar: Look up in Google Scholar


Online community managers work towards building and managing communities around a given brand or topic. A risk imposed on such managers is that their community may die out and its utility diminish to users. Understanding what drives attention to content and the dynamics of discussions in a given community informs the community manager and/or host with the factors that are associated with attention. In this paper we gain insights into the idiosyncrasies that individual community forums exhibit in their attention patterns and how the factors that impact activity differ. We glean such insights by using logistic regression models for identifying seed posts and explore the effectiveness of a range of features. Our findings show that the discussion behaviour of different communities is clearly impacted by different factors.

Item Type: Conference or Workshop Item
Copyright Holders: 2012, Association for the Advancement of Artificial Intelligence
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 33227
Depositing User: Kay Dave
Date Deposited: 16 Apr 2012 09:16
Last Modified: 12 Dec 2018 06:08
Share this page:

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.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU