IRAQIDSAD: A Dataset for Benchmarking Sentiment Analysis Tasks on Iraqi Dialect based Texts

Abstract

Sentiment analysis is a widely used technique in psychology, politics, and marketing that makes use of computational linguistics and natural language processing. The main focus of this research is a thorough literature assessment on sentiment analysis that is especially used with dialectical Arabic. Different dialects have different syntax, morphology, and grammar, which makes it difficult to classify polarity in dialectical Arabic. Our Systematic literature review investigates several aspects of sentiment analysis for dialectical Arabic in order to address these problems and support scholars working on similar projects. We identify the following phases as crucial: preprocessing, feature extraction, text annotation, and the chosen methodologies. We also present a newly corpus of 14,141 Iraqi dialect Facebook comments for benchmarking all of the text sentiment analysis and polarity classification on Iraqi texts. This corpus can be considered as an invaluable tool for sentiment analysis research in Arabic language setting