Abstract
The paper explores the use of the AQJSM method, which is built upon combining the JSM and AQ methods, to identify cause-effect relationships between psychological characteristics and text parameters produced by individuals with these characteristics. The study included two groups of subjects: the “depression” group (patients with clinical depression) and the “depressiveness” group (non-clinical patients who have high scores on the Beck depression scale). The use of the AQJSM algorithm allowed discussing the problem of validity in modern research in the field of automatic network psychodiagnostics. It was found out that different sets of text parameters act as linguistic markers of clinical depression and depressiveness.
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