Прогнозирование психологических характеристик человека на основании его цифровых следов

Психология. Журнал Высшей школы экономики. 2020. Т. 17. № 1. С. 166–180.

Латынов В. В., Ovsyannikova V. V.

The article discusses the prediction of individual psychological characteristics (personality
traits, emotional states, values, motives, etc.) based on person’s digital footprints. As studies have
shown, such characteristics can be very accurately detected on the basis of various types of digital
footprints: texts, images, Internet-surfing features, the nature and duration of phone calls,
“likes” (I like), financial transactions, and changes in a person’s location. Most often, to perform
this task, textual information is used from a variety of sources (user profiles, blogs, tweets, etc.).
With vocabulary-oriented predicting of psychological characteristics, two main approaches to
text analysis are used. One, the so-called fixed (closed-vocabulary), uses a limited vocabulary
dictionary, and the other (open-vocabulary) uses an unlimited vocabulary dictionary. In the case
of a fixed approach, a certain set of words and categories is initially set, the relationship of which
with personality traits is revealed. Unlike the fixed one, in the case of using the open approach,
there is no predefined list of words, and lexical predictors of personality traits are found directly
in the course of text analysis. The greatest accuracy of predicting was achieved in the case of personality
traits of the "Big Five". According to the degree of success in predicting, they were
arranged as follows (from the most successful to the least): extraversion, openness to experience,
conscientiousness, neuroticism, agreeableness. Emotional states, values, motives, and life satisfaction
are predicted slightly worse. The simultaneous use of several types of digital footprints,
as well as more advanced procedures for collecting and analyzing data, can significantly increase
the accuracy of the prediction. Immediate and more distant prospects for research in this area are
evaluated.

Keywords: values, прогнозирование, ценности, personality traits, черты личности, prediction, emotional state, эмоциональное состояние, цифровые следы, digital footprints