Jennifer M. Larson

Networks and Interethnic Cooperation

Ethnic groups are thought to be particularly good at enforcing cooperative behavior, in part because social networks among coethnics are favorable to peer sanctioning schemes, resulting in observed outcomes like higher public goods provision in ethnically homogeneous areas and infrequent interethnic conflict. This article formalizes this process, accounting for networks that spread news relevant to sanctioning from peer to peer. It shows that impediments to intra- and interethnic cooperation arise from positions in the network that are too peripheral or too controlling: contrary to conventional wisdom, the definitive feature of networks is not density but “integration.” Some groups can only support a low volume of civil interethnic interactions due to intra-ethnic networks that are poorly integrated. These results help explain variance across homogeneous areas, identify a barrier to cooperation in heterogeneous areas, generate empirical predictions, reveal sources of improvement masked by nonnetwork models, and offer guidance for future network elicitation.

The weakness of weak ties for novel information diffusion

Weak ties are thought to facilitate the diffusion of information through social networks because of their tendency to span otherwise distant subgroups. However, this logic assumes that weak relationships have the same capacity to transmit information as those that are strong. I argue that weak ties, especially the kind that span subgroups, are often also lower-capacity. Due to a lack of trust, an unwillingness to share benefits, or a limited ability to understand one another, an individual is less likely to share novel information across these ties. In standard models of diffusion imported from epidemiology, even reduced-capacity links would still aid diffusion. However, accounting for reduced capacity in a new model of diffusion that captures realistic features of information sharing in human groups, I demonstrate that hesitation to share across weak links substantially impedes overall diffusion. Moreover, I show that the addition of weak ties to a social network can strictly reduce the extent and speed of information diffusion. Increasing density by adding weak ties can make diffusion strictly worse by crowding out the use of higher-capacity ties. I present the results of simulated information diffusion on both hypothetical networks generated to possess varying levels of density and homophily, as well as on real social networks in two Ugandan villages shown to be responsible for face-to-face information sharing.

Specifying Theories In Comparative Politics: Toward A More Thoroughly Deductive Approach

Models in political science are often poorly specified prior to testing. In practice, most analysts rely on regression analysis to determine the weights for each independent variable (causal factor) identified in the model. We demonstrate a method for determining the relative weights of causal factors prior to testing of the model. The approach makes use of expert opinions in the qualitative literature in order to construct a more completely specified model in a deductive manner prior to testing. We also demonstrate several methods for assessing the degree of confidence we might have in the model based on the relative degree of divergence among the experts concerning the causal factors.

Testing Social Science Network Theories with Online Network Data: An Evaluation of External Validity

To answer questions about the origins and outcomes of collective action, political scientists increasingly turn to datasets with social network information culled from online sources. However, a fundamental question of external validity remains untested: are the relationships measured between a person and her online peers informative of the kind of offline, “real-world” relationships to which network theories typically speak? This article offers the first direct comparison of the nature and consequences of online and offline social ties, using data collected via a novel network elicitation technique in an experimental setting. We document strong, robust similarity between online and offline relationships. This parity is not driven by shared identity of online and offline ties, but a shared nature of relationships in both domains. Our results affirm that online social tie data offer great promise for testing long-standing theories in the social sciences about the role of social networks.

Information Diffusion in Heterogeneous Groups

Standard approaches to the study of information diffusion draw on analogies to the transmission of diseases or computer viruses, and find that adding more random ties to a network increases the speed of information propagation through it. However, a person sharing information in a social network differs from a computer transmitting a virus in two important respects: a person may not have the opportunity to pass the information to every tie, and may be unwilling to pass the information to certain ties even when presented with the opportunity. Accounting for these two features reveals that, while additional random ties allow information to jump to distant regions of a network, they also change the composition of network neighborhoods. When the latter increases the proportion of neighbors to whom people are less willing to pass information, the result can be a net decrease in diffusion. I show that this is the case in heterogeneous, homophilous networks: the addition of random ties strictly impedes information dissemination, and the impediment is increasing in both original homophily and the number of new ties.

The evolutionary advantage of limited network knowledge

Groups of individuals have social networks that structure interactions within the groups; evolutionary theory increasingly uses this fact to explain the emergence of cooperation (Eshel and Cavalli-Sforza, 1982; Boyd and Richerson, 1988, 1989; Ohtsuki et al., 2006; Nowak et al., 2010; Van Veelen et al., 2012). This approach has resulted in a number of important insights for the evolution of cooperation in the biological and social sciences, but omits a key function of social networks that has persisted throughout recent evolutionary history (Apicella et al., 2012): their role in transmitting gossip about behavior within a group. Accounting for this well-established role of social networks among rational agents in a setting of indirect reciprocity not only shows a new mechanism by which the structure of networks is fitness-relevant, but also reveals that knowledge of social networks can be fitness-relevant as well. When groups enforce cooperation by sanctioning peers whom gossip reveals to have deviated, individuals in certain peripheral network positions are tempting targets of uncooperative behavior because gossip they share about misbehavior spreads slowly through the network. The ability to identify these individuals creates incentives to behave uncooperatively. Consequently, groups comprised of individuals who knew precise information about their social networks would be at a fitness disadvantage relative to groups of individuals with a coarser knowledge of their networks. Empirical work has consistently shown that modern humans know little about the structure of their own social networks and perform poorly when tasked with learning new ones. This robust empirical regularity may be the product of natural selection in an environment of strong selective pressure at the group level. Imprecise views of networks make enforcing cooperation easier.

Fuzzy Set Theory

In this chapter we present the reader with the fundamental concepts of fuzzy set theory. The basic primer on fuzzy set theory remains Zadeh’s1965 seminal work. A number of scholars have since discussed several aspects of fuzzy set theory pertinent to the social sciences. Perhaps the best overview is provided by Smithson and Verkuilen (2006). Among the more thoroughly discussed topics are the construction of fuzzy numbers (Smithson and Verkuilen, 2006; Verkuilen, 2005;Bilgic and Turksen, 1995) and fuzzy set operations (Smithson and Verkuilen, 2006).

Applying Fuzzy Set Theory to Comparative Politics

In contrast to the discipline of economics - which adopted formal, deductive approaches grounded in rational choice assumptions more than a century ago - political science remained largely normative and inductive until the 1950s. Not surprisingly, many of the first works analyzing politics using mathematical models were written by economists (for example, Downs, 1957; Olson, 1965; Buchanan and Tullock, 1962) Since then the discipline has made significant progress in the application of mathematics to a wide number of questions as growing numbers of political scientists have embraced formal approaches. This has been particularly so in the sub-fields of American government, public policy, and international relations where rational choice models have been particularly popular. In contrast, the application of formal modeling to comparative politics has not had as much traction. Owing to an area studies tradition that emphasizes description and interpretive approaches over theory building and hypothesis testing, scholars analyzing the political systems of nation-states have largely eschewed cross-regional comparisons, let alone formal, deductive models.

Why the West Became Wild: Informal Governance with Incomplete Networks

Settlers flocking to boomtowns on the American western frontier were faced with the same task that communities in weak states across the globe face in contemporary times: self-governance. Peer sanctions can enforce cooperation in these environments, but their efficacy depends on the social networks that transmit information from peer to peer. The author uses a game-theoretic model to show that peripheral network positions can generate such strong incentives to misbehave that persistent cheating occurs in equilibrium. The model reveals that groups maintaining high levels of cooperation that face shocks to their strategic environment or to their network can ratchet down into less cooperative equilibria in which the most peripheral become ostracized. Furthermore, population change that features rapid growth, high turnover, and enclave settlements can undermine cooperation. The insights from this article help to explain the trajectory of cooperation in the mining towns of the Wild West in which high levels of cooperation deteriorated as the population surged, and help to make sense of why only certain nonwhite settlers were targets of hostility and racism.

Estimating Fuzzy Policy Preferences

The spatial models presented in the last two chapters used overlapping α–cuts to determine compromises between individuals. In this chapter, we take a closer look at the assumptions implicit in such a method. In particular, we consider ways in which individuals rank alternatives in multiple dimensions.