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Identifying Influential Users on Twitter: A Case Study from Paris Attacks |
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PP: 1021-1032 |
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doi:10.18576/amis/120515
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Author(s) |
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Layal Abu Daher,
Islam Elkabani,
Rached Zantout,
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Abstract |
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| Due to the spread of technology and world wide web, Online Social media invaded every home in the world; hence, the
analysis of such networks became an important yet challenging case of study for researchers. One of the most interesting fields of
study in social network analysis is identifying influential users who are important actors in online social networks by having an impact
on others. This work investigates the problem of identifying influential users on Twitter. Since Twitter is a user-friendly interactive
platform, it became an apparent competitor to other social medias as far as user interaction. Twitter is browsed by a variety of users,
the most important are the most influential ones among them all. In order to identify influential users, a data set was collected between
December 2015 and March 2016 reflecting real tweets from the top trendy hashtags on Twitter. In this paper, different measures are
used such as Influence Measures, Centrality Measures and Activity Measures. In addition, Association Rule Learning has been used
to detect relationships between users. After identifying the influential users from Association Rule Learning, these influential users
were compared to the results of the abovementioned measures. The results of this study indicate that identifying influential users
from Association Rule Learning and validating these identified users with the results of Influence Measures is an efficient method for
detecting the influence of users on online social networks. |
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