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Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia

Zhou, Yiwei; Demidova, Elena; Cristea, A.I.

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Authors

Yiwei Zhou

Elena Demidova



Abstract

In this paper we take an important step towards better understanding the existence and extent of entity-centric language-specific bias in multilingual Wikipedia, and any deviation from its targeted neutral point of view. We propose a methodology using sentiment analysis techniques to systematically extract the variations in sentiments associated with real-world entities in different language editions of Wikipedia, illustrated with a case study of five Wikipedia language editions and a set of target entities from four categories.

Citation

Zhou, Y., Demidova, E., & Cristea, A. (2016). Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia. In Proceedings of the 2016 ACM Symposium on Applied Computing : Artificial Intelligence and Agents, Distributed Systems, and Information Systems (750-757). https://doi.org/10.1145/2851613.2851858

Presentation Conference Type Conference Paper (Published)
Conference Name SAC 2016, 31st ACM Symposium on Applied Computing
Acceptance Date Nov 23, 2015
Online Publication Date Apr 4, 2016
Publication Date Apr 4, 2016
Deposit Date Jul 11, 2018
Publicly Available Date Jul 31, 2018
Volume 1
Pages 750-757
Book Title Proceedings of the 2016 ACM Symposium on Applied Computing : Artificial Intelligence and Agents, Distributed Systems, and Information Systems.
DOI https://doi.org/10.1145/2851613.2851858
Public URL https://durham-repository.worktribe.com/output/1146462
Related Public URLs http://wrap.warwick.ac.uk/78604/

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Copyright Statement
© Copyright is held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2016 ACM Symposium on Applied Computing : Artificial Intelligence and Agents, Distributed Systems, and Information Systems, https://doi.org/10.1145/2851613.2851858






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