Skip to content
Conference Open access

Application Analysis of NLP Technology in Understanding Psychological Intervention for College Students

2026 · ITM Web of Conferences · Vol 88, pp. 01030 · 0 citations · 5 references

TL;DR

What can be inferred of the text content posted by students that reveals some possible emotional tendencies and mental issues is examined 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.

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

Read PDF

Similar papers

Open access Aug 2026

AI-Based Assessment of Mental Health Status in College Students through Social Network Data Analysis

AI-based analysis of social network data provides an effective, non-invasive method for assessing college students' mental health status, offering significant potential for improving mental health monitoring and prevention strategies in educational settings.

Yin Zhi, Wang-Yang Ma, Guo-Wei Yang et al. · 0 citations
Review Open access Aug 2026

A curated dataset for emotion-based analysis of students’ experiences in higher education

Understanding the emotional states of university students is essential for addressing academic performance, well-being, and institutional support. This paper presents EduAffect, a novel emotion-labeled dataset constructed from public social media posts and structured survey responses by University Students in Ghana. Th...

F. A. Acheampong, Henry Nunoo-Mensah, Richard Dei-Asamoa et al. · 0 citations
#artificial intelligence Preprint Sep 2026

An AI-Powered Culturally Aware Chatbot for Stress Detection and Wellness Support among Pakistani University Students Using NLP and Machine Learning

A new, AI-driven and culturally sensitive stress detection and wellness support system that is tailored to the context of Pakistani university students, which identified teacher-student relationship as the most predictive stress factor.

Muhammad Fahad Bashir, M. Afzal · 0 citations
Review Open access Aug 2026

Promts for neural network: Educational and genre aspects

The creation of texts by a neural network has been one of the most discussed topics in the scientific community since 2022. Experts study how language models affect various areas of our lives, and worry about the future, which will change under the influence of this technology. The academic community is also discussing...

Natalia A. Kontsevaya · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.