Abstract
Users in social networks use hashtags for various reasons, some of them being serving search purposes, gaining attention or popularity or starting new conversation - thus, creating viral memes. In this paper we address the problem of classifying these hashtags in different categories, based on whether they represent a real life event or a social network generated meme. We compute a set of language-agnostic features to aid the classification of hashtags into events and memes and we provide an extensive study of the behavior that characterizes memes and events. We focus on Twitter social network, we apply our methods on a big dataset and reveal interesting characteristics of the two classes of hashtags.
Original language | English |
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Title of host publication | ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining |
Editors | Martin Ester, Guandong Xu, Xindong Wu, Xindong Wu |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 391-394 |
Number of pages | 4 |
ISBN (Electronic) | 9781479958771 |
DOIs | |
Publication status | Published - 1 Jan 2014 |
Event | 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 - Beijing, China Duration: 17 Aug 2014 → 20 Aug 2014 |
Conference
Conference | 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014 |
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Country/Territory | China |
City | Beijing |
Period | 17/08/14 → 20/08/14 |