This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (708) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2111) New Methods (1134) Chatbots and Conversational Agents (740) Artificial Intelligence (2129)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51069, first published .
Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Authors of this article:

Ziru Fu1 Author Orcid Image ;   Yu Cheng Hsu1 Author Orcid Image ;   Christian S Chan2, 3 Author Orcid Image ;   Chaak Ming Lau4 Author Orcid Image ;   Joyce Liu1 Author Orcid Image ;   Paul Siu Fai Yip1, 5 Author Orcid Image
Article Authors Cited by (23) Tweetations (3) Metrics

Journals

  1. Prescott M, Yeager S, Ham L, Rivera Saldana C, Serrano V, Narez J, Paltin D, Delgado J, Moore D, Montoya J. Comparing the Efficacy and Efficiency of Human and Generative AI: Qualitative Thematic Analyses. JMIR AI 2024;3:e54482 View
  2. Piao Y, Chen H, Wu S, Li X, Li Z, Yang D. Assessing the performance of large language models (LLMs) in answering medical questions regarding breast cancer in the Chinese context. DIGITAL HEALTH 2024;10 View
  3. Mun I. A study of the impact of ChatGPT self-efficacy on the information seeking behaviors in ChatGPT: the mediating roles of ChatGPT characteristics and utility. Online Information Review 2025;49(2):373 View
  4. Sebo P. Use of ChatGPT to Explore Gender and Geographic Disparities in Scientific Peer Review. Journal of Medical Internet Research 2024;26:e57667 View
  5. Wang Z, Huang D, Cui J, Zhang X, Ho S, Cambria E. A review of Chinese sentiment analysis: subjects, methods, and trends. Artificial Intelligence Review 2025;58(3) View
  6. Yeung A, Hammerle F, Behrens S, Matin M, Mickael M, Litvinova O, Parvanov E, Kletecka-Pulker M, Atanasov A. Online Information About Side Effects and Safety Concerns of Semaglutide: Mixed Methods Study of YouTube Videos. JMIR Infodemiology 2025;5:e59767 View
  7. Chai C, Weng S, Feng R, Wang J, Wong Y, Wang Y. A behavioral inoculation method to improve critical takeover performance of novice drivers in conditionally automated driving. Traffic Injury Prevention 2025;26(6):642 View
  8. Kim K, Kim S. Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments about Heated Tobacco Products on Social Media: Evaluation Study. Journal of Medical Internet Research 2025;27:e63631 View
  9. Kastrati M, Imran A, Hashmi E, Kastrati Z, Daudpota S, Biba M. Unlocking language barriers: Assessing pre-trained large language models across multilingual tasks and unveiling the black box with Explainable Artificial Intelligence. Engineering Applications of Artificial Intelligence 2025;149:110136 View
  10. Scerri K, Attard M. Active travel street intervention ideas in Malta: Evaluating citizen feedback using sentiment analysis. Journal of Transport Geography 2025;126:104241 View
  11. Wang M, Ma R, Shen G, Xue J. How Large Language Models Empower the Analysis of Online Public Engagement for Mega Infrastructure Projects: Cases in Hong Kong. IEEE Transactions on Engineering Management 2025;72:1262 View
  12. Nasution A, Onan A, Murakami Y, Monika W, Hanafiah A. Benchmarking Open-Source Large Language Models for Sentiment and Emotion Classification in Indonesian Tweets. IEEE Access 2025;13:94009 View
  13. Zhao Q, Li H, Wang B, Xu P, Jin P. Unveiling Dynamic Determinants of Tourism Competitiveness: Analysis Integrating Multimodal Data and Spatiotemporal Machine Learning. Journal of Travel Research 2025 View
  14. Fu Z, Hsu Y, Chan C, Yip P. Assessing Heterogeneity in Sentiment Changes in Text-Based Counseling: Latent Class Trajectory Analysis. Journal of Medical Internet Research 2025;27:e75091 View
  15. Wong J. Artificial intelligence-supported group facilitation: emerging potentials, cautious approaches, and ethical considerations in social work practice. Social Work With Groups 2025:1 View
  16. Lin A, Liu H, Wu H. A bi-directional flow weighted regression for interpreting social media sentiment identified by large language models. International Journal of Geographical Information Science 2025:1 View
  17. Shi J, Jiang S. Toward open-source foundation model ecosystem: Impact evaluation framework and promotion mechanism. Technological Forecasting and Social Change 2025;221:124328 View
  18. Giganti P, Errichiello G, Falcone P. Exploring public discourse on green hydrogen via YouTube comments: A comparative sentiment analysis using VADER and ChatGPT. Economic Analysis and Policy 2025;88:2012 View
  19. Meng H, Yang Y, Fu W, Lee J, Li Y, Lee Y. Exploring the Human-LLM Synergy in Advancing Theory-driven Qualitative Analysis. ACM Transactions on Computer-Human Interaction 2025 View

Books/Policy Documents

  1. Ray J, Mim S, Logofatu D. Artificial Intelligence Applications and Innovations. View
  2. Tople A, Vijayakumar Bharathi S. Fifth Congress on Intelligent Systems. View

Conference Proceedings

  1. Kawamura H, Wang Z, Harima K, Yamanishi T, Miura T, Maeda Y, Okada Y, Zempo K. Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing. pSCOUTER: Time-Series Emotion Classification Using Contactless Measured Multimodal Biosignals in Medical Diagnosis View
  2. Richardson F, Villavicencio A, Menezes R. Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing. The Rephrased Reality: Analysing Sentiment Shifts in LLM-Rephrased Text View