The future of artificial intelligence: evaluating ChatGPT's performance in X sentiment prediction

Abstract

Abstract Technological advancements have significantly progressed from the inception of computers and the internet to the rise of artificial intelligence (AI), profoundly impacting various sectors such as business, education, and healthcare. Among these advancements, ChatGPT has emerged as a prominent conversational AI tool, facilitating tasks such as sentiment prediction and sector-specific decision-making. This study aims to evaluate ChatGPT's performance in analyzing public sentiment using data from X (formerly Twitter) and to propose an ethical framework for its sector-specific applications. By combining the BERT transformer model with BiLSTM, Random Forest, and K-Nearest Neighbor algorithms, the study achieves a hybrid approach to sentiment prediction, demonstrating superior performance with an accuracy of 86.7%. Furthermore, the study explores ethical considerations, such as fairness, accountability, and transparency, to address ChatGPT's adoption across industries. The findings offer insights into both the technical and ethical dimensions of ChatGPT’s integration into business, education, and healthcare sectors, emphasizing its potential for sustainable and responsible use.

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