Review of Social Media Sentiment Analysis Methods

Abstract

Social media channels (SMCs) have become vital for communication, networking, and collaboration, facilitating rapid information sharing and business advertising. SMCs gather public opinions and emotions through user-generated content, essential for sentiment analysis. Companies and researchers analyze this data to understand consumer sentiment, trends, and preferences, enabling customized marketing strategies and enhanced customer engagement. This survey examines sentiment analysis and opinion mining techniques in social media using research from 2012 to 2023, covering lexicon-based, machine learning, and deep learning models. The study reviews recent research, demonstrating the application of these methods to assess public opinions and sentiments. It provides insights into current and future sentiment analysis techniques, offering recommendations for researchers, practitioners, and policymakers. Furthermore, the review explores the future potential of real-time data processing by integrating diverse data types, highlighting the value of social media data in refining sentiment analysis.