Towards detection of influential sentences affecting reputation in Wikipedia

Zhou, Yiwei; Cristea, A.I.

Abstract

Wikipedia has become the most frequently viewed online encyclopaedia website. Some sentences in Wikipedia articles have direct and obvious impact on people's opinions towards the mentioned named entities. This paper defines and tackles the problem of reputation-influential sentence detection in Wikipedia articles from various domains. We leverage multiple lexicons, to generate domain independent features. We generate topical features and word embedding features from unlabelled dataset, to boost the classification performance. We conduct several experiments, to prove the effectiveness of these features. We further adapt a two-step binary classification method, to perform multi-classification. Our evaluation results show that this method outperforms the state-of-the-art one-vs-one multi-classification method for this problem.

Citation

Zhou, Y., & Cristea, A. (2016, December). Towards detection of influential sentences affecting reputation in Wikipedia. Presented at ACM Web Science Conference 2016, Hannover

• Presentation Conference Type: Conference Paper (published)
• Conference Name: ACM Web Science Conference 2016
• Acceptance Date: Mar 23, 2016
• Publication Date: Jan 1, 2016
• Deposit Date: Jul 11, 2018
• Publicly Available Date: Jul 31, 2018
• Pages: 244-248
• Book Title: WebSci '16 : Proceedings of the 8th ACM Conference on Web Science
• DOI: https://doi.org/10.1145/2908131.2908177
• Public URL: https://durham-repository.worktribe.com/output/1144328
• Related Public URLs: http://wrap.warwick.ac.uk/78605/