Sentiment Analysis with ChatGPT Across Domains
DOI:
https://doi.org/10.48165/dbitdjr.2024.1.01.04Keywords:
ChatGPT, Sentiment Analysis, Topic Model, Public Opinion, SWOT Analysis, Scientific Citations, App Reviews, Large Language Models, Artificial IntelligenceAbstract
This paper explores ChatGPT’s applications in sentiment analysis across various domains, including business, Reddit data, and scientific citations. It demonstrates ChatGPT’s utility in understanding customer needs and public opinion, as well as its ability to identify nuanced sentiment and biases in scholarly research evaluation. Analysis of app reviews on the Google Play Store shows predominantly positive sentiments, with models like Random Forest and SVM achieving high effectiveness. The research evaluates ChatGPT and other large language models such as Gemini and LLaMA for multilingual sentiment analysis, revealing their proficiency alongside biases and inconsistencies across languages. The study emphasizes the importance of standardized evaluation methodologies and the need for data and algorithm improvements to enhance ChatGPT’s performance and applicability in sentiment analysis.
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