A comprehensive study for Arabic Sentiment Analysis (Challenges and Applications)

Abstract

Arabic language processing works on multiple levels; less often, these complementary levels synergize well with each other. Arabic Language Sentiment Analysis (ALSA) levels consist of phonetics, morphology, syntax, lexicology, semantics, and figurative nature. The analysis of opinions and feelings is of interest in English and Indo-European languages, with little emphasis in the Arabic language, which is a language full of rhetorical characteristics and implicit meanings that have positive and negative connotations and meanings across the six linguistic levels. This paper presents a comprehensive and full proposal of a strategy for ALSA. The ALSA framework analyzes the opinions and feelings at all levels of language, in addition to the importance of building an annotated corpus, which helps to understand an Arabic sentence from the level of phonetics to the rhetorical and metonymy levels. Keywords: Semantics, Arabic Sentiment Analysis, Social sciences, Machine learning, ALSA six-level framework