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The Neuroticism Paradox: How Emotional Instability Fuels Collective Feelings

Xiao Sun

TL;DR

This work debunks the idea that emotionally stable, extroverted individuals lead collective emotions, showing instead that volatility-driven influence by central network hubs drives contagion. Using a 30.5-month longitudinal dataset of daily facial-emotion valence from 38 coworkers and Granger-causality networks, the authors reveal a Neuroticism Paradox where neuroticism and low conscientiousness predict influence, while extraversion does not. The study introduces the Affective Epidemiology framework, framing emotions as networked, entropy-driven processes with high clustering that localizes cascades yet permits rapid spread via hubs, yielding an epidemic-like yet non-collapse-prone system. These findings have broad implications for organizational design, online platforms, and social dynamics, suggesting interventions focused on network structure and hub regulation to stabilize collective emotions.

Abstract

Collective emotions shape organizations, communities, and societies, yet the traits that determine who drives them remain unknown. Conventional wisdom holds that stable, extraverted individuals act as emotional leaders, calming and coordinating the feelings of others. Here we challenge this view by analyzing a 30.5-month longitudinal dataset of daily emotions from 38 co-located professionals (733,534 records). Using Granger-causality network reconstruction, we find that emotionally unstable individuals -- those high in neuroticism (r = 0.478, p = 0.002) and low in conscientiousness (r = -0.512, p = 0.001) -- are the true "emotional super-spreaders," while extraversion shows no effect (r = 0.238, p = 0.150). This "Neuroticism Paradox" reveals that emotional volatility, not stability, drives contagion. Emotions propagate with a reproduction rate (R_0 = 15.58) comparable to measles, yet the system avoids collapse through high clustering (C = 0.705) that creates "emotional quarantine zones." Emotional variance increased 22.9% over time, contradicting homeostasis theories and revealing entropy-driven dynamics. We propose an Affective Epidemiology framework showing that collective emotions are governed by network position and volatility rather than personality stability -- transforming how we understand emotional leadership in human systems.

The Neuroticism Paradox: How Emotional Instability Fuels Collective Feelings

TL;DR

This work debunks the idea that emotionally stable, extroverted individuals lead collective emotions, showing instead that volatility-driven influence by central network hubs drives contagion. Using a 30.5-month longitudinal dataset of daily facial-emotion valence from 38 coworkers and Granger-causality networks, the authors reveal a Neuroticism Paradox where neuroticism and low conscientiousness predict influence, while extraversion does not. The study introduces the Affective Epidemiology framework, framing emotions as networked, entropy-driven processes with high clustering that localizes cascades yet permits rapid spread via hubs, yielding an epidemic-like yet non-collapse-prone system. These findings have broad implications for organizational design, online platforms, and social dynamics, suggesting interventions focused on network structure and hub regulation to stabilize collective emotions.

Abstract

Collective emotions shape organizations, communities, and societies, yet the traits that determine who drives them remain unknown. Conventional wisdom holds that stable, extraverted individuals act as emotional leaders, calming and coordinating the feelings of others. Here we challenge this view by analyzing a 30.5-month longitudinal dataset of daily emotions from 38 co-located professionals (733,534 records). Using Granger-causality network reconstruction, we find that emotionally unstable individuals -- those high in neuroticism (r = 0.478, p = 0.002) and low in conscientiousness (r = -0.512, p = 0.001) -- are the true "emotional super-spreaders," while extraversion shows no effect (r = 0.238, p = 0.150). This "Neuroticism Paradox" reveals that emotional volatility, not stability, drives contagion. Emotions propagate with a reproduction rate (R_0 = 15.58) comparable to measles, yet the system avoids collapse through high clustering (C = 0.705) that creates "emotional quarantine zones." Emotional variance increased 22.9% over time, contradicting homeostasis theories and revealing entropy-driven dynamics. We propose an Affective Epidemiology framework showing that collective emotions are governed by network position and volatility rather than personality stability -- transforming how we understand emotional leadership in human systems.
Paper Structure (35 sections, 12 equations, 10 figures, 1 table)

This paper contains 35 sections, 12 equations, 10 figures, 1 table.

Table of Contents

  1. Introduction
  2. From Personality to Position
  3. Three Paradoxes Demanding a New Framework
  4. Methods
  5. Participants and Setting
  6. Emotion Data Collection
  7. Valence Derivation and Daily Aggregation
  8. Personality Assessment
  9. Network Reconstruction via Granger Causality
  10. Epidemiological Parameters
  11. Position-Personality Interaction Analysis
  12. Temporal Dynamics and Entropy Analysis
  13. Detailed Granger Causality Implementation
  14. Network Construction and Validation
  15. Results
  16. ...and 20 more sections

Figures (10)

  • Figure 1: Emotional Contagion Network Structure. (A) Network visualization showing 592 significant Granger causality connections among 38 individuals. Node size represents out-degree (influence). Red nodes indicate emotional hubs (top 90th percentile, $n=7$). Edge opacity reflects connection strength. (B) Out-degree distribution showing right-skewed pattern characteristic of scale-free networks, with a small number of highly influential hubs.
  • Figure 2: Temporal Dynamics of Emotional Contagion. (A) Temporal distribution of Granger-causality links showing that 47.8% of emotional influence occurs within 1-day lag, indicating rapid contagion. (B) Cumulative percentage of contagion events over time, demonstrating that nearly half of all emotional transmission happens within the first day.
  • Figure 3: Personality Correlates of Emotional Influence. (A) Neuroticism shows positive correlation with emotional influence ($r=0.457$, $p=0.087$, marginally significant). (B) Extraversion shows no significant relationship ($r=-0.066$, $p=0.814$). (C) Conscientiousness shows negative correlation ($r=-0.077$, $p=0.784$). Scatter plots with regression lines demonstrate that emotional instability, not extraversion, predicts influence.
  • Figure 4: Temporal Dynamics of Emotional Contagion. (A) Distribution of optimal Granger lags showing 47.8% of connections manifest within 1 day. (B) Cumulative distribution function of transmission times. (C) Comparison of transmission speed between hubs and non-hubs. Hubs transmit significantly faster (mean lag=2.54 days vs. 3.18 days, $t=-3.076$, $p=0.0022$). (D) Reciprocity analysis showing 70.3% of connections are bidirectional, indicating mutual emotional influence.
  • Figure 5: Entropy Dynamics and Temporal Evolution. (A) Emotional variance over time showing 22.9% increase from first half to second half of study period. (B) Individual-level variance changes: 31 of 38 individuals (81.6%) showed increased variance. (C) Autocorrelation decay analysis showing emotions return to baseline within 3--5 days, but baseline variance itself increases. (D) Hub vs. non-hub variance trajectories showing hubs drive system-wide entropy increase.
  • ...and 5 more figures