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Who are you, ChatGPT? Personality and Demographic Style in LLM-Generated Content

Published: October 13, 2025 | arXiv ID: 2510.11434v1

By: Dana Sotto Porat, Ella Rabinovich

Potential Business Impact:

Computers show personalities like people.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Generative large language models (LLMs) have become central to everyday life, producing human-like text across diverse domains. A growing body of research investigates whether these models also exhibit personality- and demographic-like characteristics in their language. In this work, we introduce a novel, data-driven methodology for assessing LLM personality without relying on self-report questionnaires, applying instead automatic personality and gender classifiers to model replies on open-ended questions collected from Reddit. Comparing six widely used models to human-authored responses, we find that LLMs systematically express higher Agreeableness and lower Neuroticism, reflecting cooperative and stable conversational tendencies. Gendered language patterns in model text broadly resemble those of human writers, though with reduced variation, echoing prior findings on automated agents. We contribute a new dataset of human and model responses, along with large-scale comparative analyses, shedding new light on the topic of personality and demographic patterns of generative AI.

Repos / Data Links

Page Count
14 pages

Category
Computer Science:
Computation and Language