Sentiment analysis using machine learning: Insights, applications, and future directions

One of the fundamental fields of Natural Language Processing (NLP) is sentiment analysis (SA), which enables you to categorize textual data as either positive, negative, or neutral depending on the feelings and viewpoints expressed in the text. By synthesizing data from recent works that concentrate on methodologies, applications, and challenges, this study offers an overview of the most recent machine learning-based sentiment analysis techniques. Comparison of well-known machine learning models between CNN and LSTM, including logistic regression, support vector machines, and deep learning architectures.