A Study of ChatGPT Continuous Usage Intention Based on Random Forest and SMOTE Algorithms
- DOI
- 10.2991/978-94-6463-702-1_61How to use a DOI?
- Keywords
- Artificial Intelligence; Influencing Factors; Random Forest; SMOTE Algorithm
- Abstract
Today, we have transcended the traditional information age and shifted to the era driven by artificial intelligence. And the technology of domestic large language models such as Wenxin Yiyan is still maturing, and global user adoption is still relatively low. To further develop and enhance domestic large language models and gradually narrow the gap with internationally leading models, this paper explores the factors influencing users’ willingness to continuously engage with ChatGPT by establishing a random forest model and utilizing the SMOTE algorithm for model optimization. After implementing the model, the recall of the training set increased from 0.88 to 1.00, and the recall of the test set improved from 0.92 to 1.00, indicating a significant enhancement. In the importance ranking of various factors impacting the continuous use of ChatGPT, three most critical elements identified were whether ChatGPT meets localization needs, the availability of community support and resource richness, and the presence of a user-friendly interface. This provides valuable insights for the further development and refinement of domestic large language models.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jiarui Fan PY - 2025 DA - 2025/05/05 TI - A Study of ChatGPT Continuous Usage Intention Based on Random Forest and SMOTE Algorithms BT - Proceedings of the 2025 10th International Conference on Financial Innovation and Economic Development (ICFIED 2025) PB - Atlantis Press SP - 580 EP - 586 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-702-1_61 DO - 10.2991/978-94-6463-702-1_61 ID - Fan2025 ER -