• Corpus ID: 233296926

IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always hope in Transformers

@inproceedings{Puranik2021IIITTLTEDIEACL2021HopeSD,
  title={IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always hope in Transformers},
  author={Karthik Puranik and Adeep Hande and Ruba Priyadharshini and Sajeetha Thavareesan and Bharathi Raja Chakravarthi},
  booktitle={LTEDI},
  year={2021}
}
In a world with serious challenges like climate change, religious and political conflicts, global pandemics, terrorism, and racial discrimination, an internet full of hate speech, abusive and offensive content is the last thing we desire for. In this paper, we work to identify and promote positive and supportive content on these platforms. We work with several transformer-based models to classify social media comments as hope speech or not hope speech in English, Malayalam, and Tamil languages… 

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References

SHOWING 1-10 OF 56 REFERENCES
IIITK@LT-EDI-EACL2021: Hope Speech Detection for Equality, Diversity, and Inclusion in Tamil , Malayalam and English
This paper describes the IIITK’s team submissions to the hope speech detection for equality, diversity and inclusion in Dravidian languages shared task organized by LT-EDI 2021 workshop@EACL 2021.
Hope Speech Detection: A Computational Analysis of the Voice of Peace
TLDR
It is argued the importance of automatic identification of user-generated web content that can diffuse hostility and address this prediction task, dubbed hope-speech detection, in the context of heated discussions in a politically tense situation where two nations are at the brink of a full-fledged war.
HopeEDI: A Multilingual Hope Speech Detection Dataset for Equality, Diversity, and Inclusion
TLDR
A Hope Speech dataset for Equality, Diversity and Inclusion (HopeEDI) containing user-generated comments from the social media platform YouTube with 28,451, 20,198 and 10,705 comments in English, Tamil and Malayalam, respectively, manually labelled as containing hope speech or not is constructed.
Overview of the HASOC Track at FIRE 2020: Hate Speech and Offensive Language Identification in Tamil, Malayalam, Hindi, English and German
TLDR
This paper presents the HASOC track and its two parts, creating test collections for languages with few resources and English for comparison, and presents the tasks, the data and the main results.
IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages
TLDR
This paper approaches this challenge with various transfer learning-based models to classify a given post or comment in Dravidian languages (Malayalam, Tamil, and Kannada) into 6 categories to identify the offensive language in multilingual posts that are largely code-mixed or written in a non-native script.
Hate-Speech and Offensive Language Detection in Roman Urdu
TLDR
This study presents a lexicon of hateful words in RU, develops an annotated dataset called RUHSOLD, and proposes a novel deep learning architecture called CNN-gram for hate-speech and offensive language detection and exhibits greater robustness as compared to the baselines.
UVCE-IIITT@DravidianLangTech-EACL2021: Tamil Troll Meme Classification: You need to Pay more Attention
TLDR
This work presents an ingenious model consisting of transformer-transformer architecture that tries to attain state of the art by using attention as its main component of troll and non-troll Tamil memes.
Findings of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion
TLDR
The shared task of hope speech detection for Tamil, English, and Malayalam languages was conducted as a part of the EACL 2021 workshop on Language Technology for Equality, Diversity, and Inclusion.
Deep Learning Models for Multilingual Hate Speech Detection
TLDR
A large scale analysis of multilingual hate speech in 9 languages from 16 different sources shows that in low resource setting, simple models such as LASER embedding with logistic regression performs the best, while in high resource setting BERT based models perform better.
IIITK@DravidianLangTech-EACL2021: Offensive Language Identification and Meme Classification in Tamil, Malayalam and Kannada
This paper describes the IIITK team’s submissions to the offensive language identification, and troll memes classification shared tasks for Dravidian languages at DravidianLangTech 2021 workshop@EACL
...
...