SAMAR: a system for subjectivity and sentiment analysis of Arabic social media

Authors:
Muhammad Abdul-Mageed;Sandra Kübler;Mona Diab
Affiliations:
Indiana University, Bloomington, IN;Indiana University, Bloomington, IN;Columbia University, New York, NY
Venue:
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
Year:
2012

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Abstract

In this work, we present SAMAR, a system for Subjectivity and Sentiment Analysis (SSA) for Arabic social media genres. We investigate: how to best represent lexical information; whether standard features are useful; how to treat Arabic dialects; and, whether genre specific features have a measurable impact on performance. Our results suggest that we need individualized solutions for each domain and task, but that lemmatization is a feature in all the best approaches.