Papers › IDIAP Submission@LT-EDI-ACL2022 : Hope Speech Detection for Equality, Diversity and Inclusion
IDIAP Submission@LT-EDI-ACL2022 : Hope Speech Detection for Equality, Diversity and Inclusion
Muskaan Singh, Petr Motlicek
Social media platforms have been provoking masses of people. The individual comments affect a prevalent way of thinking by moving away from preoccupation with discrimination, loneliness, or influence in building confidence, support, and good qualities. This paper aims to identify hope in these social media posts. Hope significantly impacts the well-being of people, as suggested by health professionals. It reflects the belief to achieve an objective, discovers a new path, or become motivated to formulate pathways.In this paper we classify given a social media post, hope speech or not hope speech, using ensembled voting of BERT, ERNIE 2.0 and RoBERTa for English language with 0.54 macro F1-score (2^{st} rank). For non-English languages Malayalam, Spanish and Tamil we utilized XLM RoBERTA with 0.50, 0.81, 0.3 macro F1 score (1^{st}, 1^{st},3^{rd} rank) respectively. For Kannada, we use Multilingual BERT with 0.32 F1 score(5^{th})position. We release our code-base here: https://github.com/Muskaan-Singh/Hate-Speech-detection.git.
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