A Visual Analysis of Social Influencers and Influence in the Tourism Domain

Chiara Francalanci () and Ajaz Hussain ()
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Chiara Francalanci: Politecnico di Milano
Ajaz Hussain: Politecnico di Milano

A chapter in Information and Communication Technologies in Tourism 2015, 2015, pp 19-32 from Springer

Abstract: Abstract Identifying influencers is an important step towards understanding how information spreads within a network. In social media, hub nodes are generally considered as social influencers. Social networks follow a power-law degree distribution of nodes, with a few hub nodes and a long tail of peripheral nodes. While there exist consolidated approaches supporting the identification and characterization of hub nodes, research on the analysis of the multi-layered distribution of peripheral nodes is limited. However, influence seems to spread following multi-hop paths across nodes in peripheral network layers. This paper proposes a visual approach to the graphical representation and exploration of peripheral layers by exploiting the theory of k-shell decomposition analysis. We put forward three hypotheses that allow the graphical identification of peripheral nodes that are more likely to be influential and contribute to the spread of information. Hypotheses are tested on a large sample of tweets from the tourism domain.

Keywords: Social media; Influence; Influencers; Power law graphs (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-14343-9_2

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DOI: 10.1007/978-3-319-14343-9_2

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