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ISHFMG_TUN at StanceEval: Ensemble Method for Arabic Stance Evaluation System

Domain:

natural language processing

Record type:

paper
Creator:
AssGhoJabMar
Publisher:
Und
Host:avatar
It is essential to understand the attitude of individuals towards specific topics in Arabic language for tasks like sentiment analysis, opinion mining, and social media monitoring. However, the diversity of the linguistic characteristics of the Arabic language presents several challenges to accurately evaluate the stance. In this study, we suggest ensemble approach to tackle these challenges. Our method combines different classifiers using the voting method. Through multiple experiments, we prove the effectiveness of our method achieving significant F1-score value equal to 0.7027. Our findings contribute to promoting NLP and offer treasured enlightenment for applications like sentiment analysis, opinion mining, and social media monitoring.

Visit

doi.orgunderline.io

Tags

Computational LinguisticsNatural Language ProcessingLinguisticsFOS: Languages and literature