@inproceedings{kumari-etal-2023-ml-ai-iiitranchi,
title = "{ML}{\&}{AI}{\_}{IIITR}anchi@{LT}-{EDI}-2023: Identification of Hope Speech of {Y}ou{T}ube comments in Mixed Languages",
author = "Kumari, Kirti and
Jha, Shirish Shekhar and
Dayanand, Zarikunte Kunal and
Sharma, Praneesh",
editor = "Chakravarthi, Bharathi R. and
Bharathi, B. and
Griffith, Joephine and
Bali, Kalika and
Buitelaar, Paul",
booktitle = "Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.ltedi-1.33",
pages = "214--222",
abstract = "Hope speech analysis refers to the examination and evaluation of speeches or messages that aim to instill hope, inspire optimism, and motivate individuals or communities. It involves analyzing the content, language, rhetorical devices, and delivery techniques used in a speech to understand how it conveys hope and its potential impact on the audience. The objective of this study is to classify the given text comments as Hope Speech or Not Hope Speech. The provided dataset consists of YouTube comments in four languages: English, Hindi, Spanish, Bulgarian; with pre-defined classifications. Our approach involved pre-processing the dataset and using the TF-IDF (Term Frequency-Inverse Document Frequency) method.",
}
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<abstract>Hope speech analysis refers to the examination and evaluation of speeches or messages that aim to instill hope, inspire optimism, and motivate individuals or communities. It involves analyzing the content, language, rhetorical devices, and delivery techniques used in a speech to understand how it conveys hope and its potential impact on the audience. The objective of this study is to classify the given text comments as Hope Speech or Not Hope Speech. The provided dataset consists of YouTube comments in four languages: English, Hindi, Spanish, Bulgarian; with pre-defined classifications. Our approach involved pre-processing the dataset and using the TF-IDF (Term Frequency-Inverse Document Frequency) method.</abstract>
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%0 Conference Proceedings
%T ML&AI_IIITRanchi@LT-EDI-2023: Identification of Hope Speech of YouTube comments in Mixed Languages
%A Kumari, Kirti
%A Jha, Shirish Shekhar
%A Dayanand, Zarikunte Kunal
%A Sharma, Praneesh
%Y Chakravarthi, Bharathi R.
%Y Bharathi, B.
%Y Griffith, Joephine
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F kumari-etal-2023-ml-ai-iiitranchi
%X Hope speech analysis refers to the examination and evaluation of speeches or messages that aim to instill hope, inspire optimism, and motivate individuals or communities. It involves analyzing the content, language, rhetorical devices, and delivery techniques used in a speech to understand how it conveys hope and its potential impact on the audience. The objective of this study is to classify the given text comments as Hope Speech or Not Hope Speech. The provided dataset consists of YouTube comments in four languages: English, Hindi, Spanish, Bulgarian; with pre-defined classifications. Our approach involved pre-processing the dataset and using the TF-IDF (Term Frequency-Inverse Document Frequency) method.
%U https://aclanthology.org/2023.ltedi-1.33
%P 214-222
Markdown (Informal)
[ML&AI_IIITRanchi@LT-EDI-2023: Identification of Hope Speech of YouTube comments in Mixed Languages](https://aclanthology.org/2023.ltedi-1.33) (Kumari et al., LTEDI-WS 2023)
ACL