Quantitative Socionics

Empirical and psychometric analysis of socionic typology, with an emphasis on aggregated questionnaire statistics, semantic clustering of traits, and structural reconstruction of dichotomies, functions, and type-level patterns.

Abstract

This site is a research-oriented knowledge base and methods log focused on quantitative socionics. The content prioritizes empirical descriptions (semantic clusters, response-structure patterns, cross-trait correlations) and psychometric considerations (diagnostic strength, interdependence of indicators, and known measurement artifacts).

Much of the material is grounded in large aggregated datasets and the methodological tradition associated with V. L. Talanov’s diagnostic work, presented here in an explicitly analytical format suitable for replication and further refinement.

Questionnaire

A public research questionnaire will be the primary data-collection instrument for this project. At present, the site focuses on the analytical corpus and the underlying empirical materials.

Browse empirical materials Contact

Research sections

Basics
Definitions, interpretive conventions, and methodological context for reading the empirical analyses.
Dichotomies
Long-form trait analysis with semantic clusters, response structure, and cross-dichotomy relations.
Functions
Empirical descriptions of information elements and function-related clusters, with emphasis on measurable content.
Types
Type-level material, including trait profiles, structural notes, and comparative interpretation across types.
Small groups
Groupings and cross-type structures, treated as empirical objects rather than purely theoretical categories.
Neurosocionics
Neurophysiological and cognitive correlates as discussed in the socionics-adjacent research tradition.
Miscellaneous
Technical notes, auxiliary analyses, and supporting materials that do not fit the primary taxonomy.

Scope and caveats

  • The site emphasizes empirical structure (clusters, loadings, correlations) over “type descriptions” written for identification.
  • Where applicable, methodological artifacts are treated explicitly (e.g., social desirability / self-presentation, interdependence of dichotomies, and sample composition effects).
  • Materials are intended for research and replication; interpretations should be read as statistically grounded hypotheses rather than categorical truths.