@inproceedings{gundapu-mamidi-2021-autobots,
title = "Autobots@{LT}-{EDI}-{EACL}2021: One World, One Family: Hope Speech Detection with {BERT} Transformer Model",
author = "Gundapu, Sunil and
Mamidi, Radhika",
editor = "Chakravarthi, Bharathi Raja and
McCrae, John P. and
Zarrouk, Manel and
Bali, Kalika and
Buitelaar, Paul",
booktitle = "Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion",
month = apr,
year = "2021",
address = "Kyiv",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.ltedi-1.21/",
pages = "143--148",
abstract = "The rapid rise of online social networks like YouTube, Facebook, Twitter allows people to express their views more widely online. However, at the same time, it can lead to an increase in conflict and hatred among consumers in the form of freedom of speech. Therefore, it is essential to take a positive strengthening method to research on encouraging, positive, helping, and supportive social media content. In this paper, we describe a Transformer-based BERT model for Hope speech detection for equality, diversity, and inclusion, submitted for LT-EDI-2021 Task 2. Our model achieves a weighted averaged f1-score of 0.93 on the test set."
}
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<abstract>The rapid rise of online social networks like YouTube, Facebook, Twitter allows people to express their views more widely online. However, at the same time, it can lead to an increase in conflict and hatred among consumers in the form of freedom of speech. Therefore, it is essential to take a positive strengthening method to research on encouraging, positive, helping, and supportive social media content. In this paper, we describe a Transformer-based BERT model for Hope speech detection for equality, diversity, and inclusion, submitted for LT-EDI-2021 Task 2. Our model achieves a weighted averaged f1-score of 0.93 on the test set.</abstract>
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%0 Conference Proceedings
%T Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model
%A Gundapu, Sunil
%A Mamidi, Radhika
%Y Chakravarthi, Bharathi Raja
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv
%F gundapu-mamidi-2021-autobots
%X The rapid rise of online social networks like YouTube, Facebook, Twitter allows people to express their views more widely online. However, at the same time, it can lead to an increase in conflict and hatred among consumers in the form of freedom of speech. Therefore, it is essential to take a positive strengthening method to research on encouraging, positive, helping, and supportive social media content. In this paper, we describe a Transformer-based BERT model for Hope speech detection for equality, diversity, and inclusion, submitted for LT-EDI-2021 Task 2. Our model achieves a weighted averaged f1-score of 0.93 on the test set.
%U https://aclanthology.org/2021.ltedi-1.21/
%P 143-148
Markdown (Informal)
[Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model](https://aclanthology.org/2021.ltedi-1.21/) (Gundapu & Mamidi, LTEDI 2021)
ACL