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Enriching the feature space of transfer learning in user analysis in online social networks

  • Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network. In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.

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Author:Benjamin Zill
Advisor:Jun Sun, Steffen Staab
Document Type:Bachelor Thesis
Date of completion:2018/11/30
Date of publication:2018/12/03
Publishing institution:Universität Koblenz, Universitätsbibliothek
Granting institution:Universität Koblenz, Fachbereich 4
Release Date:2018/12/03
Number of pages:Viii, 144
Institutes:Fachbereich 4 / Institute for Web Science and Technologies
Licence (German):License LogoEs gilt das deutsche Urheberrecht: § 53 UrhG