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Identifying fine grained controversy in wikipedia edits of an article.

  • Our work finds the fine grained edits in context of neighbouring tokens in Wikipedia articles. We cluster those edits according to similar neighbouring context. We encode neighbouring context into vector space using word vectors. We evaluate clusters returned by our algorithm on extrinsic and intrinsic metric and compare it with previous work. We analyse the relation between extrinsic and intrinsic measurements of fine grained edit tokens.

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Author:Aadil Rasheed
URN:urn:nbn:de:kola-18004
Advisor:Claudia Wagner, Fabian Flöck
Document Type:Master's Thesis
Language:English
Date of completion:2019/03/01
Date of publication:2019/03/06
Publishing institution:Universität Koblenz-Landau, Universitätsbibliothek
Granting institution:Universität Koblenz-Landau, Campus Koblenz, Fachbereich 4
Date of final exam:2019/03/26
Release Date:2019/03/06
Number of pages:XI, 57
Institutes:Fachbereich 4 / Institute for Web Science and Technologies
Licence (German):License LogoEs gilt das deutsche Urheberrecht: § 53 UrhG