Literature DB >> 30958188

Fashion and art cycles are driven by counter-dominance signals of elite competition: quantitative evidence from music styles.

Peter Klimek1,2, Robert Kreuzbauer3, Stefan Thurner1,2,4,5.   

Abstract

Human symbol systems such as art and fashion styles emerge from complex social processes that govern the continuous re-organization of modern societies. They provide a signalling scheme that allows members of an elite to distinguish themselves from the rest of society. Efforts to understand the dynamics of art and fashion cycles have been placed on 'bottom-up' and 'top-down' theories. According to 'top-down' theories, elite members signal their superior status by introducing new symbols (e.g. fashion styles), which are adopted by low-status groups. In response to this adoption, elite members would need to introduce new symbols to signal their status. According to many 'bottom-up' theories, style cycles evolve from lower classes and follow an essentially random pattern. We propose an alternative explanation based on counter-dominance signalling (CDS). In CDS, elite members want others to imitate their symbols; changes only occur when outsider groups successfully challenge the elite by introducing signals that contrast those endorsed by the elite. We investigate these mechanisms using a dynamic network approach on data containing almost 8 million music albums released between 1956 and 2015. The network systematically quantifies artistic similarities of competing musical styles and their changes over time. We formulate empirical tests for whether new symbols are introduced by current elite members (top-down), randomness (bottom-up) or by peripheral groups through counter-dominance signals. We find clear evidence that CDS drives changes in musical styles. This provides a quantitative, completely data-driven answer to a century-old debate about the nature of the underlying social dynamics of fashion cycles.

Entities:  

Keywords:  cultural evolution; evolutionary dynamics; fashion cycle theory; network analysis

Mesh:

Year:  2019        PMID: 30958188      PMCID: PMC6408351          DOI: 10.1098/rsif.2018.0731

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


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