Cyberbullying Detection Task: the EBSI-LIA-UNAM System (ELU) at COLING’18 TRAC-1

Ignacio Arroyo-Fernández, Dominic Forest, Juan-Manuel Torres-Moreno, Mauricio Carrasco-Ruiz, Thomas Legeleux, Karen Joannette


Abstract
The phenomenon of cyberbullying has growing in worrying proportions with the development of social networks. Forums and chat rooms are spaces where serious damage can now be done to others, while the tools for avoiding on-line spills are still limited. This study aims to assess the ability that both classical and state-of-the-art vector space modeling methods provide to well known learning machines to identify aggression levels in social network cyberbullying (i.e. social network posts manually labeled as Overtly Aggressive, Covertly Aggressive and Non-aggressive). To this end, an exploratory stage was performed first in order to find relevant settings to test, i.e. by using training and development samples, we trained multiple learning machines using multiple vector space modeling methods and discarded the less informative configurations. Finally, we selected the two best settings and their voting combination to form three competing systems. These systems were submitted to the competition of the TRACK-1 task of the Workshop on Trolling, Aggression and Cyberbullying. Our voting combination system resulted second place in predicting Aggression levels on a test set of untagged social network posts.
Anthology ID:
W18-4417
Volume:
Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Venues:
COLING | TRAC | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
140–149
Language:
URL:
https://aclanthology.org/W18-4417
DOI:
Bibkey:
Cite (ACL):
Ignacio Arroyo-Fernández, Dominic Forest, Juan-Manuel Torres-Moreno, Mauricio Carrasco-Ruiz, Thomas Legeleux, and Karen Joannette. 2018. Cyberbullying Detection Task: the EBSI-LIA-UNAM System (ELU) at COLING’18 TRAC-1. In Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pages 140–149, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Cyberbullying Detection Task: the EBSI-LIA-UNAM System (ELU) at COLING’18 TRAC-1 (Arroyo-Fernández et al., 2018)
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PDF:
https://aclanthology.org/W18-4417.pdf