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An Evaluation of Algorithms for Centrality Analysis of Twitter Users

Posted on:2016-05-08Degree:M.SType:Thesis
University:Long Island University, The Brooklyn CenterCandidate:Alwuqaysi, BdourFull Text:PDF
GTID:2478390017481848Subject:Web Studies
Abstract/Summary:
Centrality measures of social network are important in various areas and applications; including companies that take interests in analyzing social networks. Institutions which utilize centrality find it both beneficial and rewarding. I present this paper as a master's thesis requirement as a comprehensive approach to "An Evaluation of Algorithms for Centrality Analysis of Twitter users". This thesis examines the algorithms of Floyd--Warshall, Johnson, and Brandes by applying them to a twitter data set. This thesis also provides performance evaluations to each of the three algorithms for betweenness centrality. In addition to providing a complete implementation for both Warshall and Johnson's algorithms in R environment, this thesis generates beneficial insight for businesses and organizations alike who want to know who is the central or influencer in a given specific network and which algorithm to use. Keywords: Social network analysis, Centrality analysis, Twitter, Floyd--Warshall algorithm, Johnson algorithm, Brandes' algorithm, R language.
Keywords/Search Tags:Centrality, Twitter, Algorithm, Social, Network
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