Breaking the Structural Reinforcement: An Agent-Based Model on Cultural Consumption and Social Relations. (June 2023)

• Record Type: Journal Article
• Authors: Zhong, Qiankun; Hilbert, Martin; Frey, Seth
• Is Part Of: Social science computer review. Volume 41:Number 3(2023)
• Page Start: 848
• Page End: 870
• Publication Date: 2023-06
• Subjects: sociology -- social organization -- research methodologies -- agent-based model -- social network -- simulation; Social sciences -- Data processing -- Periodicals; Computers -- Social aspects -- Periodicals; Microcomputers -- Periodicals; Sciences sociales -- Informatique -- Périodiques; Micro-ordinateurs -- Périodiques; 300.285
• DOI: 10.1177/08944393211056501
• Languages: English
• ISSNs: 0894-4393

Abstract

Theorists since Marx, Bourdieu, and DiMaggio have asked how individual choices on cultural preference interact with collective social network structure. The rise of social media in today's communication landscape motivates us to take a closer look at the involved dynamics. We designed an agent-based model to explore how different behavioral principles for cultural choice and communicative affiliation affect (1) collective consumption patterns, (2) social segregation, and (3) resilience of the emergent dynamic during exogenous distributions. We analyze the influence of individual agency on network structure, and vice versa, by simulating agents who pursue elite or popular culture, while communicating with others based on homophily or randomness. Our method allows us to go beyond specific constellations and explore the realm of theoretically possible combinations. We then used an exogenous disturbance on elite culture cost to test the resilience of social network structure. We found that only in societies where economic factors drive cultural consumption, increased access to elite culture can lead to reorganization in the social network and reduce segregation between different social groups. This is because the disturbance on consumption provides agents opportunities to connect with other social groups and opens a window for social mixing. We end by discussing how our model allows us to inform a diverse set of empirical research questions, including the cultural markets of social media, the digital divide, and the split between free misinformation and established news outlets.