Can Invisible Psychological Traits Organize Visible Network Structure? - A Complex Network Analysis of Myers–Briggs Type Indicator-Based Interaction Patterns in Anonymous Social Networks

Sep 17, 2026

Exploration of how personality traits shape interaction dynamics in anonymous online communities. This study analyzes whether Myers–Briggs Type Indicator (MBTI) categories influence network structure using 288,000+ chat messages from 6,076 users, including 940 participants who provided MBTI typing and gender. A weighted undirected network is built and evaluated with assortativity, centrality, clustering, and Louvain community detection to estimate personality-based homophily and heterophily. Results show heterophilous interactions dominate (89.3%), while modularity remains low (Q=0.2584).

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages26

Reading Time1 h 6 min

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Abstract

Keywords

1. Introduction

1.1. The Psychology of Personality and Social Interaction

1.2. Homophily and Heterophily in Social Networks

1.3. Theoretical Implications of Anonymous Int

Article Can Invisible Psychological Traits Organize Visible Network Structure? A Complex Network Analysis of Myers–Briggs Type Indicator-Based Interaction Patterns in Anonymous Social Networks Seyed Moein Ayyoubzadeh 1,† , Kourosh Shahnazari 1,† , Mohammadamin Fazli 1 , Mohammadali Keshtparvar 2 arXiv :2503 . 19704v2 [ cs . SI] 29 May 2025 1 Sharif University of Technology 2 Amirkabir University of Technology * Correspondence: [smoein.ayyoubzadeh16@sharif.edu](smoein.ayyoubzadeh16@sharif.edu) (S.M.A.); [kourosh@null.net](kourosh@null.net) (K.S.)† These authors contributed equally to this work. Abstract: Exploration of the impact of personality traits on social interactions within anonymous online communities poses a great challenge at the interface of networked social sciences and psychology. We analyze here whether Myers-Briggs Type Indicator (MBTI) personality types have any impact on the dynamics of interactions on a well-known anonymous chat system with over 288,000 messages from 6,076 users. Based on a data set including 940 users voluntarily providing MBTI typing and gender, we create a weighted undirected network and apply a range of network-science measures—such as assortativity, centrality measures, clustering coefficients, and community detection with the Louvain algorithm—to estimate the level of personality-based homophily and heterophily. Contrary to previous observations in structured social settings, our research exhibits a dominance of heterophilous interactions (89.3%), particularly among cognitively complementary types, i.e., NT (Intuitive-Thinking) and NF (Intuitive-Feeling) . However, there is still a moderate level of personality-based homophily (10.7%), notably among introverted intuitive personalities (e.g., INTJ, INFP, INFJ), reflecting an underlying cognitive alignment that takes place regardless of identity markers. The interaction network exhibits scale-free properties (with a power-law exponent α = 1.45), with high-degree hubs supporting communication among various personality types. Notably, individuals with intermediate MBTI categories often serve as bridging personalities, having high centrality scores and fostering community cohesion. In contrast, gender is a stronger homophily attribute, as evidenced through much stronger levels of female users’ group interactions compared with male users’ group interactions. While MBTI type influences minor preferences for interactions, community structure is low on modularity (Q = 0.2584) with dynamics being influenced mostly through loose patterns of conversations and not through following types strictly. The findings show that, in the absence of identity cues, psychological traits subtly shape online behavior, combining exploratory heterophily with subtle homophilic inclinations. This study offers a generalizable framework for the integration of personality theory with cutting-edge network analysis and implies important implications for the design of social media platforms that are both personality-sensitive and privacy-aware. Keywords: Complex networks; Anonymous social networks; Personality-driven interaction; Myers–Briggs Type Indicator; Homophily and heterophily; Assortativity; Community detection; Scale-free networks; Social topology; Psychological trait analysis; MBTI 1. Introduction 1.1. The Psychology of Personality and Social Interaction Long central to psychology, personality research has evolved from different theoretical models explaining how individual variations affect cognitive, emotional, and behavioral processes. Among these systems, the Myers-Briggs Type Indicator has become rather wellknown for its methodical classification of people into 16 personality types. Myers-Briggs Type Indicator dimensions seek to capture basic differences in human cognition and interaction preferences by developing from Carl Jung’s theory of psychological types. Although psychometric restrictions continue to cause controversy in some scien

FAQs

What data and method does the study use to analyze personality effects in anonymous networks?

It uses 288,000+ messages from 6,076 users, with 940 users providing MBTI typing and gender. The authors build a weighted undirected network and apply network-science measures plus Louvain community detection.

What is the main finding about heterophily versus homophily?

Heterophilous interactions dominate at 89.3%, especially among complementary cognitive types such as NT and NF. Homophily still appears at a moderate level (10.7%).

How do the authors interpret community structure and modularity?

The interaction network shows scale-free properties, but community structure is low in modularity (Q=0.2584). Dynamics are driven mainly by loose conversation patterns rather than strictly following MBTI types.

Sep 17, 2026

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