Research Area:  Machine Learning
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and analyzing people’s opinions, sentiments, attitudes, perceptions, etc., toward different entities such as topics, products, and services. The fast evolution of Internet-based applications like websites, social networks, and blogs, leads people to generate enormous heaps of opinions and reviews about products, services, and day-to-day activities. Sentiment analysis poses as a powerful tool for businesses, governments, and researchers to extract and analyze public mood and views, gain business insight, and make better decisions. This paper presents a complete study of sentiment analysis approaches, challenges, and trends, to give researchers a global survey on sentiment analysis and its related fields. The paper presents the applications of sentiment analysis and describes the generic process of this task. Then, it reviews, compares, and investigates the used approaches to have an exhaustive view of their advantages and drawbacks. The challenges of sentiment analysis are discussed next to clarify future directions.
Author(s) Name:  Marouane Birjali, Mohammed Kasri, Abderrahim Beni-Hssane
Journal name:  Knowledge-Based Systems
Publisher name:  Elsevier
Volume Information:  Volume 226, 17 August 2021, 107134
Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S095070512100397X