Sentiment Analysis with ChatGPT Across Domains

Authors

  • Divya Verma Assistant Professor, Sri Guru Tegh Bahadur Institute of Management & Information Technology, GGSIPU Author

DOI:

https://doi.org/10.48165/dbitdjr.2024.1.01.04

Keywords:

ChatGPT, Sentiment Analysis, Topic Model, Public Opinion, SWOT Analysis, Scientific Citations, App Reviews, Large Language Models, Artificial Intelligence

Abstract

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.  

References

Frans Sudirjo1 , Karno Diantoro2 , Jassim Ahmad AlGasawneh3, Hizbul Khootimah Azzaakiyyah4 , Abu Muna Almaududi Ausat5.

Jinqiao Zhou 1 , Ziqi Liang 2, Yuhua Fang 3 , Zhanxi Zhou B. Shawar, E.

Walid Hariri Labged Laboratory, Computer Science depart ment Badji Mokhtar Annaba University, Algeria hariri@ labged.netP.

SHWEZINSUNAING E-mail: shwezinsunaing_s@cmu.ac.th DR. PIYACHAT UDOMWONG E-mail: piyachat.u@cmu.ac. Reuben NgID1,2, Ting Yu Joanne ChowID1

Kelly La Venture Bemidji State University, kelly.laventure@bem idjistate.edu Hyun Sang An Minnesota State University, Moorhead, hyunsang.an@mnstate.edu Wooyang Kim “Minnesota State University, Moorhead”, wooyang.kim@ mnstate.edu

Gilbert Jeffson Sagala1 , Yusran Timur Samuel2

Alessio Buscemi, Daniele Proverbio Department of Industrial Engineering, University of Trento

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Published

2024-09-17

How to Cite

Sentiment Analysis with ChatGPT Across Domains. (2024). Don Bosco Institute of Technology Delhi Journal of Research, 1(1), 19–26. https://doi.org/10.48165/dbitdjr.2024.1.01.04