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

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

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2026-07-27
DOI
https://doi.org/10.1051/itmconf/20268801030/pdf
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Zehui Li
Springer Link (Chiba Institute of Technology)
Mental Health via Writing
article

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

Zehui Li
article en

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

Springer Link (Chiba Institute of Technology)
Quality Education
Openalex Percentile: Top 5%
Mental Health via Writing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.