Opinion Mining in Arabic Extremism Texts: A Systematic Literature Review

Abstract

In this paper, a systematic literature review was provided that investigated the present evidence regarding extremist words in Arabic opinion mining methods. This study aimed to perform a Systematic Literature Review (SLR) in order to detect, evaluate, and synthesize the existing evidence regarding opinion mining techniques for extremist Arabic text. From the SLR, it is evident that opinion-mining techniques have several opportunities for detecting extremism in the Arabic text. Over the past few years, multimedia sentiment analysis has gained traction as visual content is becoming more incorporated into social media networking. Opinion mining is the process of identifying, extracting, and categorizing views about anything. It is a sort of Natural Language Processing (NLP) used to track public sentiment about a certain law, policy, or marketing, for example. It entails the creation of a method for collecting and analyzing comments and opinions concerning legislation, regulations, policies, and so on that are posted on social media. The process of information extraction is critical since it is both a beneficial tool and a difficult undertaking. In this article, we have examined the recent and advanced methodologies to extract sentiment from a web-wide item, opinion-mining methods must be automated. Also, we have analyzed the novel Artificial Intelligence and lexical-based algorithms for sentiment analysis. These methodologies find better applications in the customer feedback analysis of any organization.