@inproceedings{saumya-mishra-2021-iiit,
title = "{IIIT}{\_}{DWD}@{LT}-{EDI}-{EACL}2021: Hope Speech Detection in {Y}ou{T}ube multilingual comments",
author = "Saumya, Sunil and
Mishra, Ankit Kumar",
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-1.14/",
pages = "107--113",
abstract = "Language as a significant part of communication should be inclusive of equality and diversity. The internet user`s language has a huge influence on peer users all over the world. People express their views through language on virtual platforms like Facebook, Twitter, YouTube etc. People admire the success of others, pray for their well-being, and encourage on their failure. Such inspirational comments are hope speech comments. At the same time, a group of users promotes discrimination based on gender, racial, sexual orientation, persons with disability, and other minorities. The current paper aims to identify hope speech comments which are very important to move on in life. Various machine learning and deep learning based models (such as support vector machine, logistics regression, convolutional neural network, recurrent neural network) are employed to identify the hope speech in the given YouTube comments. The YouTube comments are available in English, Tamil and Malayalam languages and are part of the task {\textquotedblleft}EACL-2021:Hope Speech Detection for Equality, Diversity and Inclusion{\textquotedblright}."
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<abstract>Language as a significant part of communication should be inclusive of equality and diversity. The internet user‘s language has a huge influence on peer users all over the world. People express their views through language on virtual platforms like Facebook, Twitter, YouTube etc. People admire the success of others, pray for their well-being, and encourage on their failure. Such inspirational comments are hope speech comments. At the same time, a group of users promotes discrimination based on gender, racial, sexual orientation, persons with disability, and other minorities. The current paper aims to identify hope speech comments which are very important to move on in life. Various machine learning and deep learning based models (such as support vector machine, logistics regression, convolutional neural network, recurrent neural network) are employed to identify the hope speech in the given YouTube comments. The YouTube comments are available in English, Tamil and Malayalam languages and are part of the task “EACL-2021:Hope Speech Detection for Equality, Diversity and Inclusion”.</abstract>
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%0 Conference Proceedings
%T IIIT_DWD@LT-EDI-EACL2021: Hope Speech Detection in YouTube multilingual comments
%A Saumya, Sunil
%A Mishra, Ankit Kumar
%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 saumya-mishra-2021-iiit
%X Language as a significant part of communication should be inclusive of equality and diversity. The internet user‘s language has a huge influence on peer users all over the world. People express their views through language on virtual platforms like Facebook, Twitter, YouTube etc. People admire the success of others, pray for their well-being, and encourage on their failure. Such inspirational comments are hope speech comments. At the same time, a group of users promotes discrimination based on gender, racial, sexual orientation, persons with disability, and other minorities. The current paper aims to identify hope speech comments which are very important to move on in life. Various machine learning and deep learning based models (such as support vector machine, logistics regression, convolutional neural network, recurrent neural network) are employed to identify the hope speech in the given YouTube comments. The YouTube comments are available in English, Tamil and Malayalam languages and are part of the task “EACL-2021:Hope Speech Detection for Equality, Diversity and Inclusion”.
%U https://aclanthology.org/2021.ltedi-1.14/
%P 107-113
Markdown (Informal)
[IIIT_DWD@LT-EDI-EACL2021: Hope Speech Detection in YouTube multilingual comments](https://aclanthology.org/2021.ltedi-1.14/) (Saumya & Mishra, LTEDI 2021)
ACL