Event attendance classification in social media

de Lira, V. M., Macdonald, C. , Ounis, I. , Perego, R., Renso, C. and Times, V. C. (2019) Event attendance classification in social media. Information Processing and Management, 56(3), pp. 687-703. (doi:10.1016/j.ipm.2018.11.001)

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Abstract

Popular events are well reflected on social media, where people share their feelings and discuss their experiences. In this paper, we investigate the novel problem of exploiting the content of non-geotagged posts on social media to infer the users’ attendance of large events in three temporal periods: before, during and after an event. We detail the features used to train event attendance classifiers and report on experiments conducted on data from two large music festivals in the UK, namely the VFestival and Creamfields events. Our classifiers attain very high accuracy with the highest result observed for the Creamfields festival ( ∼ 91% accuracy at classifying users that will participate in the event). We study the most informative features for the tasks addressed and the generalization of the learned models across different events. Finally, we discuss an illustrative application of the methodology in the field of transportation.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ounis, Professor Iadh and Macdonald, Dr Craig
Authors: de Lira, V. M., Macdonald, C., Ounis, I., Perego, R., Renso, C., and Times, V. C.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Information Processing and Management
Publisher:Elsevier
ISSN:0306-4573
ISSN (Online):1873-5371
Published Online:10 January 2019
Copyright Holders:Copyright © 2018 Elsevier Ltd.
First Published:First published in Information Processing and Management 56(3): 687-703
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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