Table 1: Types of Sentiment ClassificationTable 2: Types of Sentiment Analysis Techniques/AlgorithmsTable 3: Literature Review Summary Table

In the digital era, sentiment analysis—also referred to as opinion mining or emotion AI—is a key tool for determining client sentiment. This paper offers a thorough overview of the most recent methods, uses, and difficulties in sentiment analysis. It includes a range of strategies, including deep learning models, sentiment lexicons, machine learning techniques, and algorithms. The vast range of applications in marketing, managing brand reputation, analyzing customer feedback, analyzing political sentiment, and improving customer service are all covered in this essay. Also covered are the difficulties with sentiment analysis, including sarcasm recognition, linguistic nuance, linguistic and cultural differences, as well as data imbalance and bias. Researchers and practitioners can enhance sentiment analysis methods and create more precise models in this quickly developing field by tackling these issues.