Detecting Aggressors and Bullies on Twitter
Author:
Affiliation:
1. Aristotle University of Thessaloniki, Thessaloniki, Greece
2. Telefonica Research, Barcelona, Spain
3. University College London, London, United Kingdom
Funder
H2020-MSCA-RISE of the European Union
Publisher
ACM Press
Reference9 articles.
1. D. Chatzakou, N. Kourtellis, J. Blackburn, E. D. Cristofaro, G. Stringhini, and A. Vakali. Mean Birds: Detecting Aggression and Bullying on Twitter. goo.gl/MSJIw7, 2017.
2. C. Chen, J. Zhang, X. Chen, Y. Xiang, and W. Zhou. 6 million spam tweets: A large ground truth for timely Twitter spam detection. In ICC IEEE, 2015.
3. M. Dadvar, D. Trieschnigg, and F. de Jong. Experts and machines against bullies: A hybrid approach to detect cyberbullies. In CAIAC, pages 275--281, 2014.
4. N. Djuric, J. Zhou, R. Morris, M. Grbovic, V. Radosavljevic, and N. Bhamidipati. Hate Speech Detection with Comment Embeddings. In WWW, 2015.
5. J. Fleiss et al. Measuring nominal scale agreement among many raters. Psychological Bulletin, 76(5), 1971.
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