Identifying Trolls and Determining Terror Awareness Level in Social Networks Using a Scalable Framework
Mutlu, Busra and Mutlu, Merve and Oztoprak, Kasim and Dogdu, Erdogan
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Abstract
Trolls in social media are `malicious' users trying to propagate an
opinion or distort the general perceptions. Identifying trolls in social
media is a task of interest for many big data applications since data
cannot be analyzed effectively without eliminating such users from the
crowd. In this paper, we present a solution for troll detection and also
the results of measuring terror awareness among social media users. We
used Twitter platform only, and applied several machine learning
techniquees and big data methodologies. For machine learning we used
k-Nearest Neighbour (kNN), Naive Bayes, and C4.5 decision tree
algorithms. Hadoop/Mahout and Hadoop/Hive platforms were used for big
data processing. Our tests show that C4.5 has a better performance on
troll detection.... Show more Show less