@inproceedings{ponnusamy-etal-2023-vel-lt,
title = "{VEL}@{LT}-{EDI}-2023: Automatic Detection of Hope Speech in {B}ulgarian Language using Embedding Techniques",
author = "Ponnusamy, Rahul and
S, Malliga and
Thavareesan, Sajeetha and
Priyadharshini, Ruba and
Chakravarthi, Bharathi Raja",
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-1.27",
pages = "179--184",
abstract = "Many people may find motivation in their lives by spreading content on social media that is encouraging or hopeful. Creating an effective model that helps in accurately predicting the target class is a challenging task. The problem of Hope speech identification is dealt with in this work using machine learning and deep learning methods. This paper presents the description of the system submitted by our team(VEL) to the Hope Speech Detection for Equality, Diversity, and Inclusion(HSD-EDI) LT-EDI-RANLP 2023 shared task for the Bulgarian language. The main goal of this shared task is to identify the given text into the Hope speech or Non-Hope speech category. The proposed method used the H2O deep learning model with MPNet embeddings and achieved the second rank for the Bulgarian language with the Macro F1 score of 0.69.",
}
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<abstract>Many people may find motivation in their lives by spreading content on social media that is encouraging or hopeful. Creating an effective model that helps in accurately predicting the target class is a challenging task. The problem of Hope speech identification is dealt with in this work using machine learning and deep learning methods. This paper presents the description of the system submitted by our team(VEL) to the Hope Speech Detection for Equality, Diversity, and Inclusion(HSD-EDI) LT-EDI-RANLP 2023 shared task for the Bulgarian language. The main goal of this shared task is to identify the given text into the Hope speech or Non-Hope speech category. The proposed method used the H2O deep learning model with MPNet embeddings and achieved the second rank for the Bulgarian language with the Macro F1 score of 0.69.</abstract>
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%0 Conference Proceedings
%T VEL@LT-EDI-2023: Automatic Detection of Hope Speech in Bulgarian Language using Embedding Techniques
%A Ponnusamy, Rahul
%A S, Malliga
%A Thavareesan, Sajeetha
%A Priyadharshini, Ruba
%A Chakravarthi, Bharathi Raja
%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 ponnusamy-etal-2023-vel-lt
%X Many people may find motivation in their lives by spreading content on social media that is encouraging or hopeful. Creating an effective model that helps in accurately predicting the target class is a challenging task. The problem of Hope speech identification is dealt with in this work using machine learning and deep learning methods. This paper presents the description of the system submitted by our team(VEL) to the Hope Speech Detection for Equality, Diversity, and Inclusion(HSD-EDI) LT-EDI-RANLP 2023 shared task for the Bulgarian language. The main goal of this shared task is to identify the given text into the Hope speech or Non-Hope speech category. The proposed method used the H2O deep learning model with MPNet embeddings and achieved the second rank for the Bulgarian language with the Macro F1 score of 0.69.
%U https://aclanthology.org/2023.ltedi-1.27
%P 179-184
Markdown (Informal)
[VEL@LT-EDI-2023: Automatic Detection of Hope Speech in Bulgarian Language using Embedding Techniques](https://aclanthology.org/2023.ltedi-1.27) (Ponnusamy et al., LTEDI-WS 2023)
ACL
- Rahul Ponnusamy, Malliga S, Sajeetha Thavareesan, Ruba Priyadharshini, and Bharathi Raja Chakravarthi. 2023. VEL@LT-EDI-2023: Automatic Detection of Hope Speech in Bulgarian Language using Embedding Techniques. In Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion, pages 179–184, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.