Possibilities of automatic text analysis in the task of determining the psychological characteristics of the author

Abstract

Using a tool for automatic text analysis and machine learning methods developed at the Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, the first results are obtained in the task of identifying text parameters specific to people with certain psychological characteristics. The tool of corpus linguistic and statistical research, based on the use of relational-situational analysis, psycholinguistic indicators and dictionaries covering the vocabulary of emotional and rational assessment, allowed us to obtain values for 177 textual attributes of the essay written by 486 subjects. To obtain data on the severity of characterological and personality characteristics of the subjects, a number of psychological questionnaires were used. When processing the data, binary classification algorithms were used — the support vector method (SVM) and the Random Forest method. The results allow us to draw conclusions about the prospects of using some textual parameters in problems of population psychodiagnostics and the adequacy of the applied classification algorithms.

Methodology for Identifying the Author of Text Information for Solving Cybersecurity Tasks

“…В настоящее время наблюдается повышенный интерес к количественным методам анализа текстовой информации на основе слабо контролируемых человеком характеристик текста, общих для всех авторов. С развитием методов текстового анализа, в работах по определению авторства начинает превалировать использование семантической информации о тексте [7], наряду с лексическими, морфологическими и синтаксическими признаками.…”

“…Каждый автор в момент создания текста представляется набором атрибутов, которые можно описать как: C a = (id,age,gender,emo,status,action,pop) ∈ ID×AGE×GENDER×EMO×STATUS×ACTION×POP, (7) где:…”