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)

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: Macdonald, Professor Craig and Ounis, Professor Iadh
• 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