Diffusion and Inequality
Social scientists have long been interested in the diffusion of innovations - the process by which new ideas, behavior, and practices spread between persons, organizations, and even countries. While innovations can enter a community through various channels, ongoing spread of innovations through a community occurs through the medium of social networks - collections of interpersonal or digital relationships connecting actors to each other. Social networks are important for diffusion because relationships foster communication, trust, and flow of information. Diffusion outcomes are also shaped by the structural properties of social networks such as density, centrality, and strength of ties, as well as properties of the innovation and the actors involved in the process.
In a recently published at Sociology Compass, I offer an overview of the these processes of diffusion of innovations through social networks. The purpose of the article is twofold: (1) to take stock of the field and review ongoing debates on the role of social networks in the diffusion of innovations and (2) to summarize the sociological implications of the diffusion of innovations through social networks.
In a paper published in Social Forces, I argue that inequality between groups can be maintained through the construction and legitimation of cultural differences. I draw on Blau’s multiform heterogeneity and complex contagion models to develop a diffusion mechanism that shows how inequality can be preserved over time when additional, new bases of differentiating between groups layer over existing ones.
I investigate the conditions under which (1) variations in the distribution of the population across stratified groups, (2) homophily of social networks along the attribute of stratification and, (3) size of personal networks interact in such a way that a practice becomes widespread in one group but not the other. Using mathematical and agent-based models, I find that inequality-preservation is more likely when ego networks are small in size and homophily is high; ego networks are larger in size and homophily is lower; and conditional on homophily and ego network size, when initial adopters happen to be disproportionately present in the dominant population group. The analysis suggests that, in addition to threshold and network structural effects as shown by previous research, Blau’s social systemic factors of population distribution and the level of homophily are important determinants of diffusion outcomes.