Humans' propensity to cooperate is driven by our embeddedness in social networks. A key mechanism through which networks promote cooperation is clustering. Within clusters, conditional cooperators are insulated from exploitation by noncooperators, allowing them to reap the benefits of cooperation. Dynamic networks, where ties can be shed and new ties formed, allow for the endogenous emergence of clusters of cooperators. Although past work suggests that either reputation processes or network dynamics can increase clustering and cooperation, existing work on network dynamics conflates reputations and dynamics. Here we report results from a large-scale experiment (total = 2,675) that embedded participants in clustered or random networks that were static or dynamic, with varying levels of reputational information. Results show that initial network clustering predicts cooperation in static networks, but not in dynamic ones. Further, our experiment shows that while reputations are important for partner choice, cooperation levels are driven purely by dynamics. Supplemental conditions confirmed this lack of a reputation effect. Importantly, we find that when participants make individual choices to cooperate or defect with each partner, as opposed to a single decision that applies to all partners (as is standard in the literature on cooperation in networks), cooperation rates in static networks are as high as cooperation rates in dynamic networks. This finding highlights the importance of structured relations for sustained cooperation, and shows how giving experimental participants more realistic choices has important consequences for whether dynamic networks promote higher levels of cooperation than static networks.

A drive-through customer pays for the order of the next customer in line, sparking a cascade of nearly 400 customers paying it forward (Phippen 2014). A farmer helps build a neighbor's barn without payment, confident that neighbors will help him when the need arises, a tradition with roots in colonial America and still practiced in Amish and Mennonite communities (Kadushin 2012). A prisoner shares his drugs with fellow inmates, not knowing whether or when they will reciprocate (Mjåland 2014). A researcher agrees to do a time-intensive peer review, with the understanding-or perhaps hope-that future papers she submits will receive similarly careful reviews. A hunter-gatherer gives meat to others, without 747290A SRXXX10.

Racial stratification is well documented in many spheres of social life. Much stratification research assumes that implicit or explicit bias on the part of institutional gatekeepers produces disparate racial outcomes. Research on status-based expectations provides a good starting point for theoretically understanding racial inequalities. In this context it is understood that race results in differential expectations for performance, producing disparate outcomes. But even here, the mechanism (i.e., status-based expectations) is often assumed due to the lack of tools to measure status-based expectations. In this article, we put forth a new way to measure implicit racial status beliefs and theorize how they are related to consensual beliefs about what “most people” think. This enables us to assess the mechanisms in the relationship between race and disparate outcomes. We conducted two studies to assess our arguments. Study 1 demonstrates the measurement properties of the implicit status measure. Study 2 shows how implicit status beliefs and perceptions of what “most people” think combine to shape social influence. We conclude with the implications of this work for social psychological research, and for racial stratification more generally.

Research on the evolution of cooperation in networked populations has assumed that ties are simply present or absent. Here we bring relational sociological insights about the strength of ties to bear on the problem of cooperation in dynamic networks. We argue that the value of ties affects their strength, which in turn promotes cooperation. We evaluate this argument with two studies. First, results from an agent-based model are consistent with the logic of our argument and are robust across a variety of initial conditions. Second, results from a controlled laboratory experiment with human participants support the key predictions. Across both studies we demonstrate that tie strength, operationalized as relationship duration, mediates the impact of tie value on cooperation.

Identifying communities or clusters in networked systems has received much attention across the physical and social sciences. Most of this work focuses on single layer or one-mode networks, including social networks between people or hyperlinks between websites. Multilayer or multi-mode networks, such as affiliation networks linking people to organizations, receive much less attention in this literature. Common strategies for discovering the community structure of multi-mode networks identify the communities of each mode simultaneously. Here I show that this combined approach is ineffective at discovering community structures when there are an unequal number of communities between the modes of a multi-mode network. I propose a dual-projection alternative for detecting communities in multi-mode networks that overcomes this shortcoming. The evaluation of synthetic networks with known community structures reveals that the dual-projection approach outperforms the combined approach when there are a different number of communities in the various modes. At the same time, results show that the dual-projection approach is as effective as the combined strategy when the number of communities is the same between the modes.

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