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From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter

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In the context of community detection in online social media, a lot of effort has been put into the definition of sophisticated network clustering algorithms and much less on the equally crucial process of obtaining high-quality input data. User-interaction data explicitly provided by social media platforms has largely been used as the main source of data because of its easy accessibility. However, this data does not capture a fundamental and much more frequent type of participatory behavior where users do not explicitly mention others but direct their messages to an invisible audience following a common hashtag. In the context of multiplex community detection, we show how to construct an additional data layer about user participation not relying on explicit interactions between users, and how this layer can be used to find different types of communities in the context of Twitter political communication.
Original languageEnglish
Title of host publication2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
PublisherIEEE
Publication date2018
ISBN (Print)978-1-5386-6052-2
ISBN (Electronic)978-1-5386-6051-5
DOIs
Publication statusPublished - 2018
Event2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) - Bercelona, Spain
Duration: 28 Aug 201831 Aug 2018

Conference

Conference2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
LandSpain
ByBercelona
Periode28/08/201831/08/2018

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