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  1. Visualizing Stochastic Actor-based Model Microsteps

    This visualization provides a dynamic representation of the microsteps involved in modeling network and behavior change with a stochastic actor-based model. This video illustrates how (1) observed time is broken up into a series of simulated microsteps and (2) these microsteps serve as the opportunity for actors to change their network ties or behavior. The example model comes from a widely used tutorial, and we provide code to allow for adapting the visualization to one’s own model.

  2. A Novel Measure of Moral Boundaries: Testing Perceived In-group/Out-group Value Differences in a Midwestern Sample

    The literature on group differences and social identities has long assumed that value judgments about groups constitute a basic form of social categorization. However, little research has empirically investigated how values unite or divide social groups. The authors seek to address this gap by developing a novel measure of group values: third-order beliefs about in- and out-group members, building on Schwartz value theory. The authors demonstrate that their new measure is a promising empirical tool for quantifying previously abstract social boundaries.
  3. Urban Hospitals as Anchor Institutions: Frameworks for Medical Sociology

    Recent policy developments are forcing many hospitals to supplement their traditional focus on the provision of direct patient care by using mechanisms to address the social determinants of health in local communities. Sociologists have studied hospital organizations for decades, to great effect, highlighting key processes of professional socialization and external influences that shape hospital-based care. New methods are needed, however, to capture more recent changes in hospital population health initiatives in their surrounding neighborhoods.
  4. Social Space Diffusion: Applications of a Latent Space Model to Diffusion with Uncertain Ties

    Social networks represent two different facets of social life: (1) stable paths for diffusion, or the spread of something through a connected population, and (2) random draws from an underlying social space, which indicate the relative positions of the people in the network to one another. The dual nature of networks creates a challenge: if the observed network ties are a single random draw, is it realistic to expect that diffusion only follows the observed network ties? This study takes a first step toward integrating these two perspectives by introducing a social space diffusion model.
  5. No Longer Discrete: Modeling the Dynamics of Social Networks and Continuous Behavior

    The dynamics of individual behavior are related to the dynamics of the social structures in which individuals are embedded. This implies that in order to study social mechanisms such as social selection or peer influence, we need to model the evolution of social networks and the attributes of network actors as interdependent processes. The stochastic actor-oriented model is a statistical approach to study network-attribute coevolution based on longitudinal data. In its standard specification, the coevolving actor attributes are assumed to be measured on an ordinal categorical scale.