Latent Space and Social Psychological Models of Diffusion

The problem of social diffusion has animated sociological thinking on topics ranging from the spread of an idea, an innovation or a disease, to the foundations of collective behavior and political polarization. While network diffusion has been a productive metaphor, the reality of diffusion processes is often muddier. Ideas and innovations diffuse differently from diseases, but, with a few exceptions, the diffusion of ideas and innovations has been modeled under the same assumptions as the diffusion of disease. In this dissertation, I develop two new diffusion models for "socially meaningful" contagions that address two of the most significant problems with current diffusion models: (1) that contagions can only spread along observed ties, and (2) that contagions do not change as they spread between people. I augment insights from these statistical and simulation models with an analysis of an empirical case of diffusion - the use of enterprise collaboration software in a large technology company. I focus the empirical study on when people abandon innovations, a crucial, and understudied aspect of the diffusion of innovations. Using timestamped posts, I analyze when people abandon software to a high degree of detail.

To address the first problem, I suggest a latent space diffusion model. Rather than treating ties as stable conduits for information, the latent space diffusion model treats ties as random draws from an underlying social space, and simulates diffusion over the social space. Theoretically, the social space model integrates both actor ties and attributes simultaneously in a single social plane, while incorporating schemas into diffusion processes gives an explicit form to the reciprocal influences that cognition and social environment have on each other. Practically, the latent space diffusion model produces statistically consistent diffusion estimates where using the network alone does not, and the diffusion with schemas model shows that introducing some cognitive processing into diffusion processes changes the rate and ultimate distribution of the spreading information. To address the second problem, I suggest a diffusion model with schemas. Rather than treating information as though it is spread without changes, the schema diffusion model allows people to modify information they receive to fit an underlying mental model of the information before they pass the information to others. Combining the latent space models with a schema notion for actors improves our models for social diffusion both theoretically and practically.

The empirical case study focuses on how the changing value of an innovation, introduced by the innovations' network externalities, influences when people abandon the innovation. In it, I find that people are least likely to abandon an innovation when other people in their neighborhood currently use the software as well. The effect is particularly pronounced for supervisors' current use and number of supervisory team members who currently use the software. This case study not only points to an important process in the diffusion of innovation, but also suggests a new approach -- computerized collaboration systems -- to collecting and analyzing data on organizational processes.

Institutions, Innovation, and Grassroots Change: Alternatives to Transnational Governance in the Global South

Transnational governance has been advanced as a viable option for regulating commodities produced in emerging economies—where incapable or unwilling states may undersupply institutions requisite for overseeing supply chains consistent with the quality, safety, environmental, or social standards demanded by the global marketplace. Producers from these jurisdictions, otherwise left with few venues for securing market access and price premiums, ostensibly benefit from whatever pathways transnational actors offer to minimize barriers to entry—including voluntary certification for compliance with a panoply of public and private rules, such as those promulgated by NGOs like the Fair Trade Federation or multinational retailers like Wal-Mart. Yet, such transnational “sustainability” governance may neither be effective nor desirable. Regulatory schemes, like third-party certification, often privilege the interests of primary architects and beneficiaries—private business associations, governments, NGOs, and consumers in the global North—over regulatory targets—producers in the global South. Rather than engaging with the international marketplace via imported and externally-driven schemes, some producer groups are instead challenging existing rules and innovating homegrown institutions. These alternatives to commercialization adopt some institutional characteristics of their transnational counterparts yet deliver benefits in a manner more aligned with the needs of producers. Drawing on original empirical cases from Nicaragua and Mexico, this dissertation examines the role of domestic institutional alternatives to transnational governance in enhancing market access, environmental quality and rural livelihoods within producer communities. Unlike the more technocratic and expert-driven approaches characteristic of mainstream governance efforts, these local regulatory institutions build upon the social capital, indigenous identity, “ancestral” knowledge, and human assets of producer communities as new sources of power and legitimacy in governing agricultural commodities.

Inequality, the Welfare State, and Demographic Change

This dissertation is a three-part analysis examining how the welfare state in advanced Western democracies has responded to recent demographic changes. Specifically, this dissertation investigates two primary relationships, beginning with the influence of government spending on poverty. I analyze two at-risk populations in particular: immigrants and children of single mothers. Next, attention is turned to the influence of individual and environmental traits on preferences for social spending. I focus specifically on religiosity, religious beliefs and religious identity. I pool data from a number of international macro- and micro-data sources including the Luxembourg Income Study (LIS), International Social Survey Program (ISSP), the World Bank Databank, and the OECD Databank. Analyses highlight the power of the welfare state to reduce poverty, but also the effectiveness of specific areas of spending focused on addressing new social risks. While previous research has touted the strength of the welfare state, my analyses highlight the need to consider new social risks and encourage closer attention to how social position affects preferences for the welfare state.