海南师范大学学报（自然科学版）2025，Vol.38Issue(3)：289-295,7.DOI:10.12051/j.issn.1674-4942.2025.03.005
基于大语言模型的高校学生焦虑心理分析
Psychological Analysis of College Students' Anxiety Based on Large Language Model
摘要
Abstract
The psychological analysis of college students'anxiety on the social media platform is helpful to detect the men-tal health problems of college students in time.However,due to the large scale of data and the high frequency of release,it is still a challenge to analyze of college students'anxiety based on social media data.The large language model is leading the development of artificial intelligence into a new era,and has shown excellent performance in dialogue,understanding and reasoning of natural language.This study investigated the large language model-based approaches for psychological analysis in college students'anxiety,with comparative evaluation of fine-tuned GPT-family and BERT-family models.The results showed that GPT-3.5 Turbo 0125 and RoBERTa-base were the two models with the best performance in the two model families,respectively.The overall performance of GPT-3.5 Turbo 0125 was better,and its precision rate reached 96.27%.In general,the large language models of GPT and BERT families have shown great potential in the psychological analysis of college students'anxiety,which provides theoretical reference and technical support for generative artificial in-telligence to help college students'mental health education.关键词
焦虑心理/高校学生/大语言模型/GPT模型/BERT模型Key words
anxiety psychology/college student/large language model/GPT model/BERT model分类
信息技术与安全科学引用本文复制引用
肖吴,王曙,刘雨平,叶鹏..基于大语言模型的高校学生焦虑心理分析[J].海南师范大学学报（自然科学版）,2025,38(3):289-295,7.基金项目
江苏高校哲学社会科学研究一般项目(2022SJYB2125) （2022SJYB2125）
教育部产学合作协同育人项目(230804691081731) （230804691081731）
