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2022 EMNLP EMNLP 2022

SI2M & AIOX Labs at WANLP 2022 Shared Task: Propaganda Detection in Arabic, A Data Augmentation and Name Entity Recognition Approach

Abstract

AbstractThis paper presents SI2M & AIOX Labs work among the propaganda detection in Arabic text shared task. The objective of this challenge is to identify the propaganda techniques used in specific propaganda fragments. We use a combination of data augmentation, Name Entity Recognition, rule-based repetition detection, and ARBERT prediction to develop our system. The model we provide scored 0.585 micro F1-Score and ranked 6th out of 12 teams.

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Kamel Gaanoun , Imade Benelallam

Topics

Machine Learning > Application Areas > Data Augmentation Natural Language Processing > Understanding > Named Entity Recognition Natural Language Processing > Applications > Text Classification Machine Learning > Learning Types > Classification Machine Learning > Learning Types > Data Augmentation

Keywords

text classification data augmentation named entity recognition propaganda detection transformer model rule-based detection propaganda technique identification
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