Book chapter Q3
Page rank versus katz: is the centrality algorithm choice relevant to measure user influence in Twitter?
Hugo Rosa (Rosa, H.); João Paulo Carvalho (Carvalho, J. P.); Ramon Fernandez Astudillo (Astudillo, R.); Fernando Batista (Batista, F.);
Book Title
Interactions Between Computational Intelligence and Mathematics. Studies in Computational Intelligence
Year (definitive publication)
2018
Language
English
Country
Switzerland
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Abstract
Microblogs, such as Twitter, have become an important socio-political analysis tool. One of the most important tasks in such analysis is the detection of relevant actors within a given topic through data mining, i.e., identifying who are the most influential participants discussing the topic. Even if there is no gold standard for such task, the adequacy of graph based centrality tools such as PageRank and Katz is well documented. In this paper, we present a case study based on a "London Riots'' Twitter database, where we show that Katz is not as adequate for the task of important actors detection since it fails to detect what we refer to as "indirect gloating'', the situation where an actor capitalizes on other actors referring to him.
Acknowledgements
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Keywords
Page rank,Katz,User influence,Twitter,Data mining
  • Computer and Information Sciences - Natural Sciences
Funding Records
Funding Reference Funding Entity
PTDC/IVC-ESCT/4919/2012 Fundação para a Ciência e a Tecnologia
UID/CEC/50021/2013 Fundação para a Ciência e a Tecnologia