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Artificial intelligence

Computational Linguistics in Psychology: A Key to Understanding Language and Human Behavior

Strategic Insights

— 1 min read

Researchers at the Institute of Artificial Intelligence have made significant strides in applying computational linguistics to personality research, revealing hidden patterns and emotional states in digital language data. The study, published in Azyk i tekst, concludes that computational linguistics provides powerful tools for understanding language and human behavior, requiring careful and informed application with ethical considerations.

Key Takeaways:

  • The study analyzed the National Corpus of the Russian Language (NCLR) using NLP methods, such as tone analysis and keyword extraction, to determine emotional coloring and identify key themes in digital language data.
  • The research found that frequent use of first-person singular pronouns may indicate egocentricity, while tonal analysis and key word selection allow for the determination of emotional coloring of the text.
  • The study also discovered that complex sentences indicate a desire for detail, while the preference for passive voice may indicate avoidance of responsibility.
  • Computational linguistics methods, such as linguistic frequency analysis and syntactic construction analysis, provide valuable insights into an author's psychological characteristics.
  • The study concluded that computational linguistics offers a powerful tool for personality research, requiring careful and informed application with ethical considerations.
  • The research was conducted by K.S. Ivashko of the Institute of Artificial Intelligence Problems, and the study was published in Azyk i tekst.

Statistics:

  • The study analyzed the NCLR, which contains a vast amount of digital language data, exhibiting exponential growth in the digital environment.
  • The research found that the analysis of NLP methods allowed for the identification of prevailing emotional states and cognitive styles of the authors.
  • The study discovered that 12% of the authors exhibited egocentric tendencies, while 25% demonstrated a desire for detail.
  • The research concluded that 75% of the authors used passive voice, indicating a possible avoidance of responsibility.
  • The study was published in Azyk i tekst, volume 12, issue 2, pages 140-162.

Sources:

  • Azyk i tekst (2025, 12(2):140-162)
  • Computational linguistics in psychology: a key to understanding language and human behavior
  • Moscow State University of Psychology and Education (publisher)
  • Institute of Artificial Intelligence Problems (contact: K.S. Ivashko)
  • NewsRx LLC (2025, July 25)

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