Directed links in social media determine the flow of information and, hence, indicate a user's influence. This paper proposes a novel visual framework to explore Twitter's ‘Who Follows Who’ relationships, by browsing the friends’ network to identify key influencers based on the actual influence of the content they share. We have developed NavigTweet, a visualization tool for the influence-based exploration of Twitter network. NavigTweet embeds a force-directed algorithm to display the graph in a multi-clustered way. To assess the user experience with NavigTweet, we have conducted a pre-release qualitative pilot study. We also report on the study and results of post-release user feedback survey.

Influence-based Twitter browsing with NavigTweet

Francalanci C.;
2017-01-01

Abstract

Directed links in social media determine the flow of information and, hence, indicate a user's influence. This paper proposes a novel visual framework to explore Twitter's ‘Who Follows Who’ relationships, by browsing the friends’ network to identify key influencers based on the actual influence of the content they share. We have developed NavigTweet, a visualization tool for the influence-based exploration of Twitter network. NavigTweet embeds a force-directed algorithm to display the graph in a multi-clustered way. To assess the user experience with NavigTweet, we have conducted a pre-release qualitative pilot study. We also report on the study and results of post-release user feedback survey.
2017
Graph visualization; Power-law graphs; Social Media Influence; Social Media Influencers; Twitter analytics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1103190
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