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Opinion Leaders in Star-Like Social Networks: A Simple Case?

Authors:
Michael Spranger
Florian Heinke
Hanna Siewerts
Joshua Hampl
Dirk Labudde

Keywords: Forensic; Opinion Leader; Graph Theory

Abstract:
In recent years, the automated, efficient and sensitive monitoring of social networks has become increasingly important for criminal investigations and crime prevention. Previously, we have shown that the detection of opinion leaders is of great interest in forensic applications. In the present study, it is argued that state of the art opinion leader detection methods have weaknesses if networks exhibit star-like social graph topology, whereas these topologies result from the interaction of users with similar interests. This is typically the case for Facebook pages of political organizations. In these cases, the underlying topologies are highly focused on one (or only a few) central actor(s) and lead to less meaningful results by classic measures of node centrality commonly used for leader detection. The presents study examines these aspects closer and exemplifies them with the help of data collected from the Facebook page of a German political party for five consecutive months. Furthermore, a quantitative indicator for describing star-like network topologies is introduced and discussed. This measure can be of great value in assessing the applicability of established leader detection methods. Finally, a modified LeaderRank score is proposed -- the CompetenceRank -- which aims to address discussed problems.

Pages: 33 to 38

Copyright: Copyright (c) IARIA, 2018

Publication date: July 22, 2018

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-654-5

Location: Barcelona, Spain

Dates: from July 22, 2018 to July 26, 2018