A Comparative Analysis of ChatGPT-4, ChatGPT-3.5, and Bard (Gemini Pro) in Sarcasm Detection

Authors

  • Navadeep Budda Mentor High School
  • Naveen Budda Mentor

DOI:

https://doi.org/10.47611/jsrhs.v13i2.6497

Keywords:

Sarcasm Detection, Artificial Intelligence, Natural Language Processing, AI Language Models, Comparative Analysis

Abstract

Understanding nuanced human communication like sarcasm is a significant challenge in the rapidly evolving domains of artificial intelligence (AI) and natural language processing (NLP). This study aims to comparatively analyze the sarcasm detection capabilities of three advanced AI models: ChatGPT-4, ChatGPT-3.5, and Bard (Gemini Pro). Utilizing the Sarcasm Corpus V2, focused on general sarcasm, the research involved testing 100 sentences (50 sarcastic and 50 non-sarcastic) with each model to assess their detection accuracy.

The results indicated distinct performance variations among the models. ChatGPT-4 and Bard showed a relatively balanced ability in identifying both sarcastic and non-sarcastic sentences, whereas ChatGPT-3.5 exhibited a stronger accuracy in detecting non-sarcastic sentences but struggled with sarcastic ones. Statistical analysis confirmed that the differences in performance were significant (p < 0.05).

These findings have critical implications for the development and application of AI in fields requiring nuanced language understanding, such as social media analysis, customer service, and sentiment analysis. The study highlights the varying strengths and weaknesses of current AI models in processing complex linguistic constructs like sarcasm and underscores the need for continued advancements in this area.

Conclusively, this research provides valuable insights into the current state of sarcasm detection in AI, contributing to the broader understanding of AI's language processing capabilities. It also opens avenues for future research, particularly in enhancing AI algorithms for improved sarcasm detection across diverse contexts and languages

Downloads

Download data is not yet available.

Author Biography

Naveen Budda, Mentor

Accomplished technology professional with an impressive 26-year tenure in EY, specializing in the hands-on design and execution of multimillion-dollar technology projects across diverse domains such as Finance, Mobility, Talent, Risk, and Brand Marketing and Communication portfolios. Renowned for successful management of a unified HR solution implementation across 141 countries and for elevating customer satisfaction through optimal application deployment. Led the establishment of a team with a focus on leveraging AI capabilities within the Talent domain, resulting in the successful completion of several highly effective projects. A forward-thinking leader who thrives outside the comfort zone, building high-performing teams, and demonstrating a commitment to continuous learning with 11 EY Badges and current MS studies in Data Analytics at Georgia Tech.

References or Bibliography

aboobaker, J., & Ilavarasan, E. (2020). A survey on sarcasm detection and challenges. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). https://doi.org/10.1109/icaccs48705.2020.9074163

Blasko, D. G., Kazmerski, V. A., & Dawood, S. S. (2021). Saying what you don’t mean: A cross-cultural study of perceptions of sarcasm. Canadian Journal of Experimental Psychology / Revue Canadienne de Psychologie Expérimentale, 75(2), 114–119. https://doi.org/10.1037/cep0000258

Kumar, A., Dikshit, S., & Albuquerque, V. H. (2021). Explainable artificial intelligence for sarcasm detection in dialogues. Wireless Communications and Mobile Computing, 2021, 1–13. https://doi.org/10.1155/2021/2939334

Oraby, S., Harrison, V., Reed, L., Hernandez, E., Riloff, E., & Walker, M. (2016). Creating and characterizing a diverse corpus of sarcasm in dialogue. Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue. https://doi.org/10.18653/v1/w16-3604

Parameswaran, P., Trotman, A., Liesaputra, V., & Eyers, D. (2021). Detecting the target of sarcasm is hard: Really?? Information Processing & Management, 58(4), 102599. https://doi.org/10.1016/j.ipm.2021.102599

Rahaman, Md. S., Ahsan, M. M., Anjum, N., Terano, H. J., & Rahman, Md. M. (2023). From CHATGPT-3 to GPT-4: A significant advancement in AI-driven NLP Tools. Journal of Engineering and Emerging Technologies, 1(1), 50–60. https://doi.org/10.52631/jeet.v1i1.188

Published

05-31-2024

How to Cite

Budda, N., & Budda, N. (2024). A Comparative Analysis of ChatGPT-4, ChatGPT-3.5, and Bard (Gemini Pro) in Sarcasm Detection. Journal of Student Research, 13(2). https://doi.org/10.47611/jsrhs.v13i2.6497

Issue

Section

HS Research Articles