Topic-centric Classification of Twitter User's Political Orientation

Fang, A., Ounis, I. , Habel, P., Macdonald, C. and Limsopatham, N. (2015) Topic-centric Classification of Twitter User's Political Orientation. In: 38th Annual ACM SIGIR Conference (SIGIR 2015), Santiago, Chile, 9-13 Aug 2015, pp. 791-794. ISBN 9781450336215 (doi:10.1145/2766462.2767833)

Fang, A., Ounis, I. , Habel, P., Macdonald, C. and Limsopatham, N. (2015) Topic-centric Classification of Twitter User's Political Orientation. In: 38th Annual ACM SIGIR Conference (SIGIR 2015), Santiago, Chile, 9-13 Aug 2015, pp. 791-794. ISBN 9781450336215 (doi:10.1145/2766462.2767833)

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Abstract

In the recent Scottish Independence Referendum (hereafter, IndyRef), Twitter offered a broad platform for people to express their opinions, with millions of IndyRef tweets posted over the campaign period. In this paper, we aim to classify people's voting intentions by the content of their tweets---their short messages communicated on Twitter. By observing tweets related to the IndyRef, we find that people not only discussed the vote, but raised topics related to an independent Scotland including oil reserves, currency, nuclear weapons, and national debt. We show that the views communicated on these topics can inform us of the individuals' voting intentions ("Yes"--in favour of Independence vs. "No"--Opposed). In particular, we argue that an accurate classifier can be designed by leveraging the differences in the features' usage across different topics related to voting intentions. We demonstrate improvements upon a Naive Bayesian classifier using the topics enrichment method. Our new classifier identifies the closest topic for each unseen tweet, based on those topics identified in the training data. Our experiments show that our Topics-Based Naive Bayesian classifier improves accuracy by 7.8% over the classical Naive Bayesian baseline.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Macdonald, Dr Craig and Ounis, Professor Iadh and Limsopatham, Mr Nut and Habel, Dr Philip
Authors: Fang, A., Ounis, I., Habel, P., Macdonald, C., and Limsopatham, N.
College/School:College of Science and Engineering > School of Computing Science
College of Social Sciences > School of Social and Political Sciences > Politics
ISBN:9781450336215
Copyright Holders:Copyright © 2015 ACM
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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