A Comparative Sentiment Analysis on ChatGPT Reviews using Machine Learning Models

Sentiment analysis is a field within natural language processing that seeks to recognize and extract personal and emotional data from textual information, including feelings, viewpoints, and attitudes. Reviews have now turned into an indispensable data source for both consumers and businesses. Analyzing the sentiment of such reviews can offer valuable ideas into customers' likes, contentment, and discontentment. In recent times, Chat Generative Pre-trained Transformer (ChatGPT) has paved new paths in the area of Artificial Intelligence and Natural Language Processing. In our work, sentiment of people is analyzed through reviews taken from people of various age groups from different educational backgrounds to understand the efficiency of ChatGPT. A comparative analysis was carried out by using four different machine learning models and two hybrid models using SVM + Decision Tree and Random Forest + Logistic Regression. The survey also analyzed various effects of using ChatGPT and how it contributes in making people lethargic and decreases logical thinking ability and problem-solving skills.