From semantic memory to collective creativity: A generative cognitive foundation for social creativity models

TL;DR

This paper introduces a multi-level socio-cognitive agent-based framework that models how social structure and cognitive mechanisms interact to produce collective creativity, revealing emergent phenomena without explicit programming.

Contribution

It presents a novel agent-based model linking semantic memory structures to social creativity, enabling mechanistic insights into cognition and social interactions.

Findings

Lower pre-interaction ideation overlap predicts larger stimulation gains

Shared inspiration sources induce network-level redundancy

Framework enables mechanistic theory-building about cognition and social structure

Abstract

Simulation-based theory development has yielded powerful insights into collective performance by linking social structure to emergent outcomes, yet it has struggled to extend to collective creativity. Creativity is hard to capture purely at the social level, as novel ideas are generated through cognitive mechanisms. To address this gap, we introduce a multi-level socio-cognitive agent-based framework in which agents share a common semantic vocabulary and substrate but differ in semantic network topology. A single generative parameter tunes semantic modularity, yielding emergent individual differences in ideational breadth. When agents exchange ideation traces, two canonical social-creativity phenomena arise without being imposed: lower pre-interaction ideation overlap predicts larger stimulation gains, and shared inspiration sources induce network-level redundancy. The framework enables mechanistic theory-building about cognition and social structure in collective creativity.