Clustering user behaviour patterns on Twitter Online publication date: Sat, 04-Mar-2017
by Christine Klotz; Coskun Akinalp; Herwig Unger
International Journal of Social Network Mining (IJSNM), Vol. 2, No. 3, 2016
Abstract: Personalised systems and targeted services must be tailored to the characteristics of the individual. Several categorisations for Twitter users exist, but all fail to account for the complexity of human beings. Behaviour is a key feature in detecting users with specific characteristics. This study demonstrates how to extract meaningful user behaviour patterns on large-scale datasets that reflect the personalities of human users. This is a first step to prediction of user action and the underlying individual decision-making process.
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