Morphology based arabic sentiment analysis of Book reviews

Abstract

Sentiment analysis is a fundamental natural language processing task that automatically analyzes raw textual data and infer from it semantic meaning. The inferred information focuses on the author’s attitude or opinion towards a written text. Although there is extensive research done on sentiment analysis on English language, there has been little work done that targets the morphologically rich structure of the Arabic language. In addition, most of the research done on Arabic either focus on introducing new datasets or new sentiment lexicons. We propose a supervised sentiment analysis approach for two tasks: positive/negative classification and positive/negative/neutral classification. We focus on the morphological structure of the Arabic language by introducing filtering, segmentation and morphological processing specifically for this language. We also manually create an emoticon sentiment lexicon in order to stress the expressed emotions and improve on the sentiment analyzer.