| Issue |
ITM Web Conf.
Volume 88, 2026
The 2026 International Conference on Artificial Intelligence, Big Data and Computer Science (AIBDCS 2026)
|
|
|---|---|---|
| Article Number | 01030 | |
| Number of page(s) | 5 | |
| Section | Artificial Intelligence, Big Data and Computer Science | |
| DOI | https://doi.org/10.1051/itmconf/20268801030 | |
| Published online | 27 July 2026 | |
Application Analysis of NLP Technology in Understanding Psychological Intervention for College Students
School of Mathematical Sciences, Huaqiao University, Quanzhou, 362021, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Given that the majority of university students are interested in mental health problems within their academic and social lives, how to apply state-of-the-art technologies for timely detection and response to the mental risks is becoming an active research area. NLP is the field that aims to understand texts, recognize sentiments in them, and perform deep semantics understanding. The present paper will discuss about the history and general technical structure of NLP which shows how much relevant is NLP for Psychological Health Intervention at College level. Moreover, this paper discusses the practical use of emotion analysis, monitoring of the public opinion, intelligent question answering systems, and automatic warning systems. By using the method of studying the campus wall data, this paper examines what can be inferred of the text content posted by students that reveals some possible emotional tendencies and mental issues. With these results, this paper also assesses the existing academic trends and their main challenges including the protection of data privacy and model accuracy, and envisions the further development opportunities. To sum up, the present research is intended to form a strong theoretical basis and give a useful technical perspective on enhancing the mental health education and optimizing the intervention plans in universities
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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