Language reflects individual thinking， and language disturbance reflects thought disorder. Automated analysis of language （AAL） is a computational method based on natural language processing and machine learning， which is mainly used to process and understand individual language content. Common indicators include semantic coherence and syntactic complexity. AAL is mainly used to identify schizophrenia and clinical high-risk for psychosis （CHR-P）， and predict the conversion of CHR-P. Research indicates that AAL is sensitive， accurate and objective， and better than clinical rating. This article reviews the common AAL indicators and related applications.