Sentiment analysis for Arabic language: A brief survey of approaches and techniques

TL;DR

This paper provides a comprehensive survey of Arabic sentiment analysis, discussing various approaches, techniques, challenges, and solutions specific to the Arabic language in the context of social media and online reviews.

Contribution

It offers the first detailed overview of Arabic sentiment analysis methods, highlighting key challenges and summarizing proposed solutions in the literature.

Findings

Arabic sentiment analysis faces unique linguistic challenges.

Various machine learning and lexicon-based techniques have been applied.

Significant progress has been made despite language-specific difficulties.

Abstract

With the emergence of Web 2.0 technology and the expansion of on-line social networks, current Internet users have the ability to add their reviews, ratings and opinions on social media and on commercial and news web sites. Sentiment analysis aims to classify these reviews reviews in an automatic way. In the literature, there are numerous approaches proposed for automatic sentiment analysis for different language contexts. Each language has its own properties that makes the sentiment analysis more challenging. In this regard, this work presents a comprehensive survey of existing Arabic sentiment analysis studies, and covers the various approaches and techniques proposed in the literature. Moreover, we highlight the main difficulties and challenges of Arabic sentiment analysis, and the proposed techniques in literature to overcome these barriers.