Chatzakou, D;
Kourtellis, N;
Blackburn, J;
Cristofaro, ED;
Stringhini, G;
Vakali, A;
(2017)
Detecting Aggressors and Bullies on Twitter.
In: Barrett, R and Cummings, R and Agichtein, E and Gabrilovich, E, (eds.)
Proceedings of the 26th International Conference on World Wide Web Companion.
(pp. pp. 767-768).
ACM: Perth, Australia.
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Abstract
Online social networks constitute an integral part of people's every day social activity and the existence of aggressive and bullying phenomena in such spaces is inevitable. In this work, we analyze user behavior on Twitter in an effort to detect cyberbullies and cuber-aggressors by considering specific attributes of their online activity using machine learning classifiers.
| Type: | Proceedings paper |
|---|---|
| Title: | Detecting Aggressors and Bullies on Twitter |
| Event: | WWW 2017 Companion |
| ISBN-13: | 978-1-4503-4914-7 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3041021.3054211 |
| Publisher version: | http://dx.doi.org/10.1145/3041021.3054211 |
| Language: | English |
| Additional information: | © 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10046721 |
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