Are you a hero or a villain? A semantic role labelling approach for detecting harmful memes.

Shaik Fharook, Syed Sufyan Ahmed, Gurram Rithika, Sumith Sai Budde, Sunil Saumya, Shankar Biradar


Abstract
Identifying good and evil through representations of victimhood, heroism, and villainy (i.e., role labeling of entities) has recently caught the research community’s interest. Because of the growing popularity of memes, the amount of offensive information published on the internet is expanding at an alarming rate. It generated a larger need to address this issue and analyze the memes for content moderation. Framing is used to show the entities engaged as heroes, villains, victims, or others so that readers may better anticipate and understand their attitudes and behaviors as characters. Positive phrases are used to characterize heroes, whereas negative terms depict victims and villains, and terms that tend to be neutral are mapped to others. In this paper, we propose two approaches to role label the entities of the meme as hero, villain, victim, or other through Named-Entity Recognition(NER), Sentiment Analysis, etc. With an F1-score of 23.855, our team secured eighth position in the Shared Task @ Constraint 2022.
Anthology ID:
2022.constraint-1.3
Volume:
Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
CONSTRAINT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
19–23
Language:
URL:
https://aclanthology.org/2022.constraint-1.3
DOI:
10.18653/v1/2022.constraint-1.3
Bibkey:
Cite (ACL):
Shaik Fharook, Syed Sufyan Ahmed, Gurram Rithika, Sumith Sai Budde, Sunil Saumya, and Shankar Biradar. 2022. Are you a hero or a villain? A semantic role labelling approach for detecting harmful memes.. In Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations, pages 19–23, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Are you a hero or a villain? A semantic role labelling approach for detecting harmful memes. (Fharook et al., CONSTRAINT 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.constraint-1.3.pdf
Video:
 https://aclanthology.org/2022.constraint-1.3.mp4