Transition to Adulthood is an essential life stage for many families. The prior research has shown that young people with intellectual or development disabil-ities (IDD) have more challenges than their peers. This study is to explore how to use natural language processing (NLP) methods, especially unsupervised machine learning, to assist psychologists to analyze emotions and sentiments and to use topic modeling to identify common issues and challenges that young people with IDD and their families have. Additionally, the results were compared to those obtained from young people without IDD who were in tran-sition to adulthood. The findings showed that NLP methods can be very useful for psychologists to analyze emotions, conduct cross-case analysis, and sum-marize key topics from conversational data. Our Python code is available at https://github.com/mlaricheva/emotion_topic_modeling.

本研究旨在探索如何使用自然语言处理（NLP）方法，尤其是无监督机器学习，来帮助心理学家分析情绪和情感，并使用话题建模来识别智力或发展障碍者的年轻人及其家庭所面临的共同问题和挑战。研究发现，NLP方法可用于帮助心理学家分析情绪，进行交叉案例分析并从对话数据中总结关键话题。

智力或发育障碍青少年的成年过渡：情感检测和主题建模