SubmissionNumber#=%=#29
FinalPaperTitle#=%=#RDproj at SemEval-2024 Task 4: An Ensemble Learning Approach for Multilingual Detection of Persuasion Techniques in Memes
ShortPaperTitle#=%=#
NumberOfPages#=%=#7
CopyrightSigned#=%=#Yuhang Zhu
JobTitle#==#
Organization#==#
Abstract#==#This paper introduces our bagging-based ensemble learning approach for the SemEval-2024 Task 4 Subtask 1, focusing on multilingual persuasion detection within meme texts. This task aims to identify persuasion techniques employed within meme texts, which is a hierarchical multilabel classification task. The given text may apply multiple techniques, and persuasion techniques have a hierarchical structure. However, only a few prior persuasion detection systems have utilized the hierarchical structure of persuasion techniques. In that case, we designed a multilingual bagging-based ensemble approach, incorporating a soft voting ensemble strategy to effectively exploit persuasion techniques' hierarchical structure. Our methodology achieved the second position in Bulgarian and North Macedonian, third in Arabic, and eleventh in English.
Author{1}{Firstname}#=%=#Yuhang
Author{1}{Lastname}#=%=#Zhu
Author{1}{Username}#=%=#johan_zhu
Author{1}{Email}#=%=#tjuzhuyuhang@outlook.com
Author{1}{Affiliation}#=%=#Uppsala University

==========
èéáğö