Modeling the empathy-self-discovery paradox in Gen Z social behavior with NPD using artificial neural networks

Area of Science:

• Psychology
• Sociology
• Computational Social Science

Background:

• The Myers-Briggs Type Indicator (MBTI) is experiencing a resurgence among Generation Z.
• This phenomenon is theorized to be a social code addressing an
• empathy-self-discovery paradox
• linked to narcissistic traits.
• The MBTI's appeal may stem from fulfilling needs for belonging and enabling performative self-presentation, aligning with narcissistic dynamics like validation-seeking.

Purpose of the Study:

• To investigate the MBTI's popularity in Generation Z.
• To explore its connection to narcissistic personality traits and the
• empathy-self-discovery paradox
• .
• To analyze the role of social media in this phenomenon using computational modeling.

Main Methods:

• Mixed-methods approach combining neuroimaging and clinical literature on Narcissistic Personality Disorder (NPD).
• Development of an Artificial Neural Network (ANN) model to analyze behavioral data.
• Mapping non-linear relationships between social media engagement, MBTI usage, and outcomes like self-discovery and socialization.

Main Results:

• Social media interaction is the primary driver of MBTI popularity, serving as a source of narcissistic supply.
• Self-discovery exhibits a non-linear relationship with engagement, declining with excessive use.
• Excessive MBTI use may promote a superficial, label-based identity, consistent with narcissistic identity diffusion.

Conclusions:

• The online MBTI phenomenon reflects a conflict between genuine self-exploration and instrumental identity use for social capital.
• Digital platforms may foster identity markets that resonate with and exacerbate narcissistic psychosocial patterns.
• Bridging neuropsychological insights with computational modeling offers a novel framework for understanding these dynamics.