Abstract: Social Media Sentiment Analysis (SMSA) has become an essential tool for organizations aiming to understand public perception through digital expressions. This study investigates advanced sentiment analysis techniques using Natural Language Processing (NLP) and Machine Learning (ML) models from 2020 to 2025. It highlights real-time applications, modeling strategies, and the efficacy of various sentiment classification algorithms. The paper also discusses the impact of deep learning and transformer-based models in improving accuracy and reliability. Our analysis confirms the growing relevance of SMSA in strategic decision-making across sectors including marketing, politics, and crisis management.
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DOI:
10.17148/IJARCCE.2025.14546
