SubmissionNumber#=%=#19
FinalPaperTitle#=%=#AAST-NLP at ClimateActivism 2024: Ensemble-Based Climate Activism Stance and Hate Speech Detection : Leveraging Pretrained Language Models
ShortPaperTitle#=%=#
NumberOfPages#=%=#
CopyrightSigned#=%=#
JobTitle#==#
Organization#==#
Abstract#==#Climate activism has emerged as a powerful force in addressing the urgent challenges posed by climate change. Individuals and organizations passionate about environmental issues use platforms like Twitter to mobilize support, share information, and advocate for policy changes. Unfortunately, amidst the passionate discussions, there has been an unfortunate rise in the prevalence of hate speech on the platform. Some users resort to personal attacks and divisive language, undermining the constructive efforts of climate activists. In this paper, we describe our approaches for three subtasks of ClimateActivism at CASE 2024. For all the three subtasks, we utilize pretrained language models enhanced by ensemble learning. Regarding the second subtask, dedicated to target detection, we experimented with incorporating Named Entity Recognition in the pipeline. Additionally, our models secure the second, third and fifth ranks in the three subtasks respectively.
Author{1}{Firstname}#=%=#Ahmed
Author{1}{Lastname}#=%=#El-Sayed
Author{1}{Username}#=%=#ahmedelsayed
Author{1}{Email}#=%=#a1752000@gmail.com
Author{1}{Affiliation}#=%=#Arab Academy For Science and Technology
Author{2}{Firstname}#=%=#Omar
Author{2}{Lastname}#=%=#Nasr
Author{2}{Email}#=%=#omarnasr5206@gmail.com
Author{2}{Affiliation}#=%=#Arab Academy For Science and Technology

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