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Predicting discussions on the social semantic web

Rowe, Matthew; Angeletou, Sofia and Alani, Harith (2011). Predicting discussions on the social semantic web. In: 8th Extended Semantic Web Conference (ESWC 2011), 29 May - 2 June 2011, Heraklion, Greece.

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DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1007/978-3-642-21064-8_28
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Abstract

Social Web platforms are quickly becoming the natural place for people to engage in discussing current events, topics, and policies. Analysing such discussions is of high value to analysts who are interested in assessing up-to-the-minute public opinion, consensus, and trends. However, we have a limited understanding of how content and user features can influence the amount of response that posts (e.g., Twitter messages) receive, and how this can impact the growth of discussion threads. Understanding these dynamics can help users to issue better posts, and enable analysts to make timely predictions on which discussion threads will evolve into active ones and which are likely to wither too quickly. In this paper we present an approach for predicting discussions on the Social Web, by (a) identifying seed posts, then (b) making predictions on the level of discussion that such posts will generate. We explore the use of post-content and user features and their subsequent e!ects on predictions. Our experiments produced an optimum F1 score of 0.848 for identifying seed posts, and an average measure of 0.673 for Normalised Discounted Cumulative Gain when predicting discussion levels.

Item Type: Conference Item
Copyright Holders: 2011 Springer-Verlag
ISSN: 0302-9743
Extra Information: LNCS 6644
The Semanic [sic] Web: Research and Applications
8th Extended Semantic Web conference, ESWC 2011
Heraklion, Crete, Greece, May 29-June 2, 2011
Proceedings, Part II
Grigoris Anoniou, Marko Grobelnik, Elena Simperl, Bijan Parsia, Dimitris Plexousakis, Pieter De Leenheer, Jeff Pan (eds.)
ISBN: 978-3-642-21063-1
DOI: 10.1007/978-3-642-21064-8

Academic Unit/Department: Knowledge Media Institute
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 29101
Depositing User: Kay Dave
Date Deposited: 13 Jul 2011 13:20
Last Modified: 11 Jul 2013 19:37
URI: http://oro.open.ac.uk/id/eprint/29101
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