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Revealing the political affinity of online entities through their Twitter followers

dc.contributor.authorStamatelatos, Giorgos
dc.contributor.authorGyftopoulos, Sotirios
dc.contributor.authorDrosatos, George
dc.contributor.authorEfraimidis, Pavlos S.
dc.description.abstractIn this work, we show that the structural features of the Twitter online social network can divulge valuable information about the political affinity of the participating nodes. More precisely, we show that Twitter followers can be used to predict the political affinity of prominent Nodes of Interest (NOIs) they opt to follow. We utilize a series of purely structure-based algorithmic approaches, such as modularity clustering, the minimum linear arrangement (MinLA) problem and the DeGroot opinion update model in order to reveal diverse aspects of the NOIs’ political profile. Our methods are applied to a dataset containing the Twitter accounts of the members of the Greek Parliament as well as an enriched dataset that additionally contains popular news sources. The results confirm the viability of our approach and provide evidence that the political affinity of NOIs can be determined with high accuracy via the Twitter follower network. Moreover, the outcome of an independently performed expert study about the offline political scene confirms the effectiveness of our methods.en_UK
dc.publisherElsevier Ltd.en_UK
dc.relation.ispartofseriesvol. 57;issue 2
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_UK
dc.subjectSocial network analysisen_UK
dc.subjectTwitter followersen_UK
dc.subjectNews mediaen_UK
dc.subjectPolitical affinityen_UK
dc.titleRevealing the political affinity of online entities through their Twitter followersen_UK

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© 2019 Elsevier Ltd. All rights reserved.
Except where otherwise noted, this item's license is described as © 2019 Elsevier Ltd. All rights reserved.