@inproceedings{bin-emran-etal-2024-masonperplexity,
title = "{M}ason{P}erplexity at {C}limate{A}ctivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification",
author = "Bin Emran, Al Nahian and
Ganguly, Amrita and
Puspo, Sadiya Sayara Chowdhury and
Goswami, Dhiman and
Raihan, Md Nishat",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Thapa, Surendrabikram and
Uludo{\u{g}}an, G{\"o}k{\c{c}}e},
booktitle = "Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.case-1.18",
pages = "132--138",
abstract = "The task of identifying public opinions on social media, particularly regarding climate activism and the detection of hate events, has emerged as a critical area of research in our rapidly changing world. With a growing number of people voicing either to support or oppose to climate-related issues - understanding these diverse viewpoints has become increasingly vital. Our team, MasonPerplexity, participates in a significant research initiative focused on this subject. We extensively test various models and methods, discovering that our most effective results are achieved through ensemble modeling, enhanced by data augmentation techniques like back-translation. In the specific components of this research task, our team achieved notable positions, ranking 5th, 1st, and 6th in the respective sub-tasks, thereby illustrating the effectiveness of our approach in this important field of study.",
}
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%0 Conference Proceedings
%T MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification
%A Bin Emran, Al Nahian
%A Ganguly, Amrita
%A Puspo, Sadiya Sayara Chowdhury
%A Goswami, Dhiman
%A Raihan, Md Nishat
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%Y Uludoğan, Gökçe
%S Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F bin-emran-etal-2024-masonperplexity
%X The task of identifying public opinions on social media, particularly regarding climate activism and the detection of hate events, has emerged as a critical area of research in our rapidly changing world. With a growing number of people voicing either to support or oppose to climate-related issues - understanding these diverse viewpoints has become increasingly vital. Our team, MasonPerplexity, participates in a significant research initiative focused on this subject. We extensively test various models and methods, discovering that our most effective results are achieved through ensemble modeling, enhanced by data augmentation techniques like back-translation. In the specific components of this research task, our team achieved notable positions, ranking 5th, 1st, and 6th in the respective sub-tasks, thereby illustrating the effectiveness of our approach in this important field of study.
%U https://aclanthology.org/2024.case-1.18
%P 132-138
Markdown (Informal)
[MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification](https://aclanthology.org/2024.case-1.18) (Bin Emran et al., CASE-WS 2024)
ACL