Multilevel embeddedness: The case of the global fisheries governance complex

This paper explores how bilateral and multilateral clustering are embedded in a multilevel system of interdependent networks. We argue that in complex systems in which bilateral and multilateral relations are themselves interrelated, such as global fisheries governance, embeddedness cannot be reduced to unipartite or bipartite clustering but implicates multilevel closure. We elaborate expectations for ties’ multilevel embeddedness based on network theory and substantive considerations and explore them using a multilevel ERGM. We find states’ bilateral ties are embedded in their shared membership in multilateral fisheries agreements, which is itself clustered around foci represented by similar content and treaty secretariats.     

Explaining the Sexuality Gap in Protest Participation

ABSTRACT

This study investigated the relationship between sexual orientations and the protest actions of adults in the United States. Drawing from General Social Survey data from 1996 to 2004, we found that lesbians, gays, and bisexuals were more than twice as likely to protest as heterosexuals. To account for this sexuality gap, we used Patrick Egan’s (2008) political distinctiveness theories to identify possible underlying causes of these protesting differences. After running several regressions, we found that sexuality and protesting relationships were moderated by issues of educational attainment, marital statuses, metropolitan residencies, political partisanships, governmental grievances, and gender role expectations.     

Partners,Institutions and International Currencies: The International Political Foundations for the Rise of the Renminbi

The use of an international currency is not just a natural market phenomenon; it relies heavily on international political foundations. The historical lessons of the four major international currencies—the pound, dollar, euro and yen—show that a strong partner network and a favorable international institutional environment are the two major political foundations for the formation of a stable international currency. The rise of the renminbi, as a late starter looking to become a major international currency, depends not only on the requisite economic conditions but on governmental diplomacy aimed at attracting more monetary cooperation partners and creating international institutions that support its worldwide use. This strategy reinforces the political foundations for the rise of the renminbi. Building a network of partners supporting the renminbi as an international currency and creating a system of international monetary institutions are the real tests of the issuing country’s political leadership. This political leadership capacity has three dimensions: public trust founded on reputation building; a centripetal force driven by provision of benefits; and coercive force applied through sanctions. Comparatively speaking, the renminbi is still in the early stage of its ascent, so the development of its political infrastructure should concentrate mainly on gaining public trust through reputation-building and employing centripetal force involving provision of benefits.     

Bootstrap order selection for SETAR models

In this paper, we investigate the selecting performances of a bootstrapped version of the Akaike information criterion for nonlinear self-exciting threshold autoregressive-type data generating processes. Empirical results will be obtained via Monte Carlo simulations. The quality of our method is assessed by comparison with its non-bootstrap counterpart and through a novel procedure based on artificial neural networks.     

Bayesian Network Structure Learning with Permutation Tests

In literature there are several studies on the performance of Bayesian network structure learning algorithms. The focus of these studies is almost always the heuristics the learning algorithms are based on, i.e., the maximization algorithms (in score-based algorithms) or the techniques for learning the dependencies of each variable (in constraint-based algorithms). In this article, we investigate how the use of permutation tests instead of parametric ones affects the performance of Bayesian network structure learning from discrete data. Shrinkage tests are also covered to provide a broad overview of the techniques developed in current literature.     

Latino Faces,Corporate Ties: Latino Advocacy Organizations and Their Board Membership

Although they have increased exponentially since the 1960s, social scientists know little about ethnic advocacy organizations. These nonprofits are important bridges between underresourced communities and mainstream funding organizations and their directors are established ethnic leaders. Sociologists study interlocking directorates—or shared board membership—to understand how organizations fit together within broader social networks. Network concepts, particularly the theory of institutional isomorphism, suggest that organizations are likely to be similar to the extent they are connected and operate within a common organizational field. We apply this logic to Latino advocacy organizations to examine the underlying source of cohesion across this ethnic field. We ask whether the organizations are tied by interlocking directorates of ethnic elites who sit on their boards of directors or if board members' common affiliation with other elite institutions creates the structural conditions that facilitate potential ideological or behavioral similarity. A social network analysis of five prominent Latino advocacy organizations reveals support for both hypotheses: Latino board members are both embedded in ethnic‐based networks and entrenched within elite organizational webs. This suggests that ethnic elites who sit on the boards of Latino advocacy organizations are also corporate elites, selected for the social capital they bring to these nonprofits.     

Thumbs up for privacy?: Differences in online self-disclosure behavior across national cultures

This study investigates relationships between national-level culture and online self-disclosure behavior. We operationalize culture through the GLOBE dimensions, a set of nine variables measuring cultural practices and another nine measuring values. Our observations of self-disclosure come from the privacy settings of approximately 200,000 randomly sampled Facebook users who designated a geographical network in 2009. We model privacy awareness as a function of one or more GLOBE variables with demographic covariates, evaluating the relative influence of each factor. In the top-performing models, we find that the majority of the cultural dimensions are significantly related to privacy awareness behavior. We also find that the hypothesized directions of several of these relationships, based largely on cultural attitudes towards threat mitigation, are confirmed.     

Because they were there: Access,deliberation, and the mobilization of networks for support

When people need help, what is the process through which they decide whom in their network to turn to? Research on social support has described a process that is deliberative in nature: people determine their needs, assess who in their network has the needed attributes—such as skill, trustworthiness, intimacy, and accessibility—and then activate that tie. Nevertheless, research in behavioral economics and other fields has shown that people make many decisions not deliberatively but intuitively. We examine this possibility in the context of social support by focusing on one factor: accessibility. Although researchers have argued that people weigh the accessibility of potential helpers as they do any other attribute, accessibility may be not only an attribute of the helper but also a condition of the situation. We develop a framework to make this question tractable for survey research and evaluate competing hypotheses using original data on an analytically strategic sample of ∼2000 college students, probing concrete instances of social support. We identify and document not one but three decision processes, reflective, incidental, and spontaneous activation, which differ in the extent to which actors had deliberated on whether to seek help and on whom to approach before activating the tie. We find that while the process was reflective (consistent with existing theory) when skill or trustworthiness played a role, it was significantly less so (consistent with the alternative) when accessibility did. Findings suggest that actors decide whom in their network to mobilize through at least three systematically different processes, two of which are consistent less with either active “mobilization” or explicit “help seeking” than with responsiveness to opportunity and context.     

Crowdfunding digital platforms: Backer networks and their impact on project outcomes

Crowdfunding platforms serve to connect project creators and backers. Previous research has explored several project and platform determinants that impact crowdfunding outcomes. However, there has been limited research on these determinants at an individual level. Our paper addresses how backers may influence the outcomes of projects in crowdfunding platforms. We explore several methods commonly used in the industry to identify influence and show that centrality measures through a backer affiliation network best exemplifies influence. Using data from Kickstarter, we construct a weighted backer network based on 52,678 common projects backed by 11,134 backers. Controlling for digital media mentions and project quality, we find evidence that backers in central positions within the network have a positive impact on multiple project outcomes such as the project success rates, amount of funds raised, speed of reaching the crowdfunding goal as well as the number of backers contributing to the project. These findings are replicated and reinforced by using data from a different crowdfunding platform using the entire backer network based on 1095 projects backed by 87,896 backers. Several robustness tests are used to validate these results.     

Affiliation networks with an increasing degree sequence

Affiliation network is one kind of two-mode social network with two different sets of nodes (namely, a set of actors and a set of social events) and edges representing the affiliation of the actors with the social events. Although a number of statistical models are proposed to analyze affiliation networks, the asymptotic behaviors of the estimator are still unknown or have not been properly explored. In this article, we study an affiliation model with the degree sequence as the exclusively natural sufficient statistic in the exponential family distributions. We establish the uniform consistency and asymptotic normality of the maximum likelihood estimator when the numbers of actors and events both go to infinity. Simulation studies and a real data example demonstrate our theoretical results.