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Evaluating Chatbot Performance: A Meta-Analysis Approach with Deep Learning

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  • Jsowd, Kyldo

Abstract

Chatbot technology has gained significant attention in recent years, with numerous studies focusing on developing and evaluating chatbot performance. However, due to the vast amount of research and the diversity of methodologies employed, it can be challenging to gain a comprehensive understanding of chatbot performance across different domains and applications. In this paper, we propose a meta-analysis approach to evaluate chatbot performance using deep learning techniques. The objective of this study is to systematically analyze and synthesize the findings from existing chatbot performance evaluations, providing a comprehensive assessment of chatbot capabilities and identifying factors that contribute to their success or limitations. To achieve this, we leverage deep learning models to extract valuable insights from a wide range of chatbot evaluation studies.

Suggested Citation

  • Jsowd, Kyldo, 2023. "Evaluating Chatbot Performance: A Meta-Analysis Approach with Deep Learning," OSF Preprints 593tq, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:593tq
    DOI: 10.31219/osf.io/593tq
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