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2021 EACL EACL 2021

ASAD: Arabic Social media Analytics and unDerstanding

Abstract

AbstractThis system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets. The suite is made available through a web API and a web interface where users can enter text or upload files.

🌉 Interdisciplinary Bridge — Interdisciplinary 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, Security & Privacy, Speech & Audio

Authors

Sabit Hassan , Hamdy Mubarak , Ahmed Abdelali , Kareem Darwish

Topics

Natural Language Processing > Understanding > Sentiment Analysis Natural Language Processing > Applications > Text Classification Interdisciplinary > Social > Social Media Analysis Natural Language Processing > Applications > Sentiment Analysis

Keywords

sentiment analysis text classification social media analysis offensive language detection spam detection hate speech detection dialect identification arabic nlp
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