A small world on feet of clay? A comparison of empirical small-world studies against best-practice criteria

Small-world studies were introduced by Milgram and others in the 1960s and 1970s. These studies, and a majority of variants conducted by others, display a number of methodological weaknesses that bias their results. While no explicit methodological standard exists for these studies, here I derive a number of best-practice criteria for small-world studies by pointing out mistakes of previous studies, and by applying methodological standards from other empirical research areas. Improving the methodology of letter referral studies is important, because such studies could still be useful in a number of contexts today, especially for the exploration of factors affecting targeted search processes.     

Network closure and integration in the mid-20th century American mafia

Criminal networks are thought to be biased toward decentralization and security rather than integration and efficiency. This article examines this tradeoff in a large-scale national criminal network spanning more than 700 members of 24 distinct American mafia families operating in the mid-20th century. Producing a novel network image of the American mafia as a set of highly differentiated yet intertwined islands of criminal activity, the analysis uncovers a small-world structure that allowed both for strong intragroup closure and high intergroup connectivity. This balance reflected a division of network labor in which integrative bridging connections were disproportionately concentrated among a small number of criminals. Furthermore, the criminals who held such bridging ties tended to be either low- or high-status—but not of middling status—within their respective organizations.     

The structure of educational research: The role of multivocality in promoting cohesion in an article interlock network

Researchers interested in the social and intellectual features of scholarly knowledge have emphasized the importance of small-scale, informally organized groups of people interested in the same or closely related research problems. The structure of these social networks, in large part, influences the way which research problems are identified, studied and transformed into policy. Building on popular concerns about the state of the educational research field, this study examines what its structure implies about the field's ability to integrate ideas and practices. Using data about which articles readers access from the online database of the Teachers College Record, one of the field's more popular journals, it is shown that the article interlock network exhibits a structure that fits parameters of both small-world and structurally cohesive models. Furthermore, this study unpacks the network's community structure to show that those articles that serve as the core through which much of the network is connected possess a multivocal identity; an ambiguous identity that appeals to multiple audiences simultaneously. Results are suggestive of mechanisms that could be used to promote greater cohesion across the network's distinct communities.     

An agent-based model of network effects on tax compliance and evasion

Agent-based models are flexible analytical tools suitable for exploring and understanding complex systems such as tax compliance and evasion. The agent-based model created in this research builds upon two other agent-based models of tax evasion, the Korobow et al., 2007, Hokamp and Pickhardt, 2010 models. The model utilizes their rules for taxpayer behavior and apprehension of tax evaders in order to test the effects of network topologies in the propagation of evasive behavior. Findings include that network structures have a significant impact on the dynamics of tax compliance, demonstrating that taxpayers are more likely to declare all their income in networks with higher levels of centrality across the agents, especially when faced with large penalties proportional to their incomes. These results suggest that network structures should be chosen selectively when modeling tax compliance, as different topologies yield different results. Additionally, this research analyzed the special case of a power law distribution and found that targeting highly interconnected individuals resulted in a lower mean gross tax rate than targeting disconnected individuals, due to the penalties inflating the mean gross tax rate in the latter case.     

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.     

Social networks of knowledge production in Brazilian psychology: comparing sub-areas

The social processes underlying the production of scientific knowledge make it an inherently social endeavor. The interaction between systems of thought and affiliation has been subject of the sociology of science, with remarkable developments in studies on the structure of scientific fields based on social networks analysis. Although psychology is one of the pioneer fields investigated in this literature, there is scarcity of research on psychology. The objective of this paper is to describe the social networks’ dynamics of knowledge production in psychology in Brazil, comparing association patterns among its sub-areas. For this purpose, 395 researchers responded an electronic questionnaire about their relationships. Networks of nine psychology sub-areas were analyzed for structural properties (i.e. density, centrality) and relational exchanges (the connecting roles of boundary spanners and central connectors). Findings showed different structures and connectivity patterns between networks, but most of these areas configure as small worlds. Discussion explores implications of these findings for the production of knowledge within areas, and for the national production of psychological knowledge as a whole, with effects on the international projection of knowledge produced in Brazil.     

Agent Rationality Behind Network Formation

We search for agent behavior rules which lead to the emergence of social networks that exhibit empirically observed phenomena: small-world property, scale-free degree distribution and stability in time. We assume that agents form and sever links using a cost-benefit analysis. Agents receive benefit from own links and from links that their friends form. On the other hand, link formation, deletion and keeping is costly. We find that a simple model structure which relies only on convex cost of link upkeep leads to stable networks which exhibit the small-world property.     

Social Networks of Old People in India

Summary

This article presents a comparative analysis of the available research on the social networks of older persons in India. Most of this research has been done in North Indian cities. The research foci of the available studies include network size, core networks and beyond, life course changes in networks, impacts of residency in old-age homes, gender differences, and joint and nuclear family residence. This research is discussed in terms of its policy implications. Because the research demonstrates that social networks are important for the welfare of older Indians, one can conclude that social policy that encourages the maintenance of robust networks throughout the life course may be worth pursuing. One aspect of policy is discussed. The analysis of the relationship between social network and gender suggests that current policies that can be seen as supporting gender inequality in terms of property may have a negative impact on the networks of older women.     

Network Canvas: Key decisions in the design of an interviewer-assisted network data collection software suite

Self-reported social network analysis studies are often complex and burdensome, both during the interview process itself, and when conducting data management following the interview. Through funding obtained from the National Institute on Drug Abuse (NIDA/NIH), our team developed the Network Canvas suite of software – a set of complementary tools that are designed to simplify the collection and storage of complex social network data, with an emphasis on usability and accessibility across platforms and devices, and guided by the practical needs of researchers. The suite consists of three applications: Architect: an application for researchers to design and export interview protocols; Interviewer: a touch-optimized application for loading and administering interview protocols to study participants; and Server: an application for researchers to manage the interview deployment process and export their data for analysis. Together, they enable researchers with minimal technological expertise to access a complete research workflow, by building their own network interview protocols, deploying these protocols widely within a variety of contexts, and immediately attaining the resulting data from a secure central location. In this paper, we outline the critical decisions taken in developing this suite of tools for the network research community. We also describe the work which guides our decision-making, including prior experiences and key discovery events. We focus on key design choices, taken for theoretical, philosophical, and pragmatic reasons, and outline their strengths and limitations.     

A comparison of email networks and off-line social networks: A study of a medium-sized bank

Recently there has been a surge in the availability of online data concerning the connections between people, and these online data are now widely used to map the social structure of communities. There has been little research, however, on how these new types of relational data correspond to classical measures of social networks. To fill this gap, we contrast the structure of an email network with the underlying friendship, communication, and advice seeking networks. Our study is an explorative case study of a bank, and our data contains emails among employees and a survey of the ego networks of the employees. Through calculating correlations with QAP standard errors and estimating exponential random graph (ERG) models, we find that although the email network is related to the survey-based social networks, email networks are also significantly different: while off-line social networks are strongly shaped by gender, tenure, and hierarchical boundaries, the role of these boundaries are much weaker in the email network.     

Corporate competition: A self-organized network

A substantial number of studies have extended the work on universal properties in physical systems to complex networks in social, biological, and technological systems. In this paper, we present a complex networks perspective on interfirm organizational networks by mapping, analyzing and modeling the spatial structure of a large interfirm competition network across a variety of sectors and industries within the United States. We propose two micro-dynamic models that are able to reproduce empirically observed characteristics of competition networks as a natural outcome of a minimal set of general mechanisms governing the formation of competition networks. Both models, which utilize different approaches yet apply common principles to network formation give comparable results. There is an asymmetry between companies that are considered competitors, and companies that consider others as their competitors. All companies only consider a small number of other companies as competitors; however, there are a few companies that are considered as competitors by many others. Geographically, the density of corporate headquarters strongly correlates with local population density, and the probability two firms are competitors declines with geographic distance. We construct these properties by growing a corporate network with competitive links using random incorporations modulated by population density and geographic distance. Our new analysis, methodology and empirical results are relevant to various phenomena of social and market behavior, and have implications to research fields such as economic geography, economic sociology, and regional economic development.     

Exploring the embassy sampling strategy for large-scale cross-national study in replicating the normative theory of global public relations

This study explored a new sampling strategy of using embassies as cultural enclaves for large-scale cross-national research in testing the generic status of individual excellence principles in the normative theory of global public relations. Based on survey data, the investigation looked at factorial invariance for six organizational process-related excellence principles across two cultural groups of embassies (N = 113) in Washington, D.C.: individualist and collectivist. The findings suggested that the principle of symmetric internal communication may not be generic whereas the others are universal in factor structure and further put into question the generic status of the notion of symmetry so fundamental to symmetric internal communication.     

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.     

Fashions, habits and changing preferences: Simulation of psychological factors affecting market dynamics

Markets can show different types of dynamics, from quiet markets dominated by one or few products, to markets with constant penetration of new and reintroduced products. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between similar products. Products remain in the market as long as they maintain a minimum level of market share, else they will be replaced by a new product. Assuming a population of consumats with different preferences, and social networks, the model simulates adoption of new products for alternative assumptions on behavioural rules. Furthermore, the consequences of changing preferences and the size of social networks are explored. Results show that the behavioural rules that dominate the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in and unstable renewal. Results also show the importance of psychological variables like social networks, preferences and the need for identity to explain the dynamics of markets.     

Ethical implications of network data in business and management settings

Reflecting on the compilation and analysis of a range of network datasets drawn from our own work and some prominent examples, we consider the ethical challenges in dealing with network data in business and management settings. We argue that the managerial processes that characterize such settings introduce particular ethical sensitivities in the stages of commissioning and research design, and when collecting, analyzing and reporting network data. These sensitivities arise from the imperatives of business, motivations for commissioning network analyses and the legal authority that managers have over employees. We argue that ethical considerations are much more pervasive in business and management network research than in many other fields.In this contribution, we present a range of ethical challenges in network research in business and management settings that arise at several stages of the research process. For each issue identified, we describe the ethical problem and propose mitigation remedies. From this reflection, we suggest guidelines for other researchers to consider when designing research projects in this application area.     

Fast clustering for signed graphs based on random walk gap

Signed graphs are often used as models for social media mining, social networks analysis and nature language processing. In this paper, we study clustering algorithms for signed graphs that can be scaled for use in large-scale signed networks. A proposed mechanism, called a random walk gap (RWG), is used to extract more cluster structure information. RWG uses two types of random walks on signed graphs. The first considers positive edges only. The second takes negative edges into account. Three types of edges in signed graphs are identified and their different characteristics in terms of transition probability changes are determined for the two types of random walk graphs. Different characteristics contain different information about cluster structure and a RWG matrix is used to reflect the differences. The RWG matrix is used to adjust the weights of edges in signed graphs. This is the first study to perform a random walk on negative edges. A fast clustering for signed graphs (FCSG) algorithm is then proposed. This FCSG is compared with existing methods. The computational times for different algorithms are measured. The experiments show that the proposed FCSG algorithm gives better results than existing algorithms based on the performance criteria of imbalance and modularity.     

How social ties transcend class boundaries? Network variability as tool for exploring occupational homophily

The research on social network analysis established the existence of class homophily, the tendency that personal networks are homogeneous in the class sense, as one of the governing patterns. This is explained via two main mechanisms: choice homophily and induced homophily. But the literature focused less on the question how can class boundaries be transgressed and what are the channels of class heterophily. This paper explores class heterophily on Croatian data acquired through position generator, which measures social capital (resources captured in social relations) by exploring the range of different occupational positions which are accessible to an individual (extensity index). Network variability is thereby taken as proxy for class composition of personal networks. The paper concludes that that political participation and sociability enable cross-class ties, since this offers an opportunity to meet and befriend people from all walks of life; and that people on the middle of the social hierarchy have the most diverse social networks. The hypotheses that social mobility can represent a vehicle for class heterophily; and that class heterophily is more pronounced in smaller settlements, where society networks show more overlap between social circles; were confirmed only partially, and require further investigation. These findings concern class boundaries related to the notion of choice homophily. As for induced homophily, the paper concludes that here too the boundaries are not watertight, as cultural omnivores have a wider range of class contacts.     

The subjective dimension of social isolation: A qualitative investigation of older adults' experiences in small social support networks

In the aging literature, social isolation has been primarily defined in terms of reduced support network size and low frequency of social contacts. Having a small social support network is associated with social isolation and an increased risk of physical and emotional vulnerability. However, this conceptualization ignores the contributions of a host of other factors, including life experiences, family dynamics, and long-term patterns of socialization. This paper argues that alongside quantitative assessments of support systems, the application of a life course perspective is needed to understand small social networks as lived experience. We report on findings from 28 in-depth interviews with older adults identified as being at risk of social isolation on the basis of the self-reported size of their social networks. We discuss these participants' experiences in the context of significant life course transitions such as marriage and widowhood.     

Calling social capital: An analysis of the determinants of success on the TV quiz show “Who Wants to Be a Millionaire?”

This paper analyzes the determinants of successful participation of candidates on the well known television quiz show “Who Wants to Be a Millionaire?”. Our study includes a survey of 660 contestants who participated in the German version of the show between 1999 and 2007. We are particularly interested in two hypotheses. The first hypothesis refers to the assumed advantage of social capital. Contestants on the show have the option of calling a friend (the phone-a-friend lifeline) whom they select from their personal networks. The person chosen to be the phone-a-friend lifeline should be especially helpful if the contestant has a large network of able contacts from which to choose. Second, according to human capital theory the participants’ education should increase the chances of success and should lead on average to higher payoffs. Since contestants on the show can answer questions correctly mainly on the basis of their knowledge and since other characteristics of the candidates are irrelevant, estimates of the human capital effect are not affected by other possible causes suggested by signaling theory. Thus, our analysis is an assessment of the effects of social capital and human capital on the show.