The dual-projection approach for two-mode networks

There have been two distinct approaches to two-mode data. The first approach is to project the data to one-mode and then analyze the projected network using standard single-mode techniques, also called the conversion method. The second approach has been to extend methods and concepts to the two-mode case and analyze the network directly with the two modes considered jointly. The direct approach in recent years has been the preferred method since it is assumed that the conversion method loses important structural information. Here we argue that this is not the case, provided both projections are used together in any analysis. We illustrate how this approach works using core/periphery, structural equivalence and centrality as examples.     

Triadic closure in two-mode networks: Redefining the global and local clustering coefficients

As the vast majority of network measures are defined for one-mode networks, two-mode networks often have to be projected onto one-mode networks to be analyzed. A number of issues arise in this transformation process, especially when analyzing ties among nodes’ contacts. For example, the values attained by the global and local clustering coefficients on projected random two-mode networks deviate from the expected values in corresponding classical one-mode networks. Moreover, both the local clustering coefficient and constraint (structural holes) are inversely associated to nodes’ two-mode degree. To overcome these issues, this paper proposes redefinitions of the clustering coefficients for two-mode networks.     

Good health and the bridging of structural holes

Bridges that span structural holes are often explained in terms of the entrepreneurial personalities or rational motivations of brokers, or structural processes that lead to the intersection of social foci. I argue that the existence and use of bridges in interpersonal networks also depends on individuals’ health. Poor health may make it more difficult to withstand the pressures and to execute some of the common tasks associated with bridging (e.g., brokerage). I examine this possibility using egocentric network data on over 2500 older adults drawn from the recent National Social Life, Health, and Aging Project (NSHAP). Multivariate regression analyses show that both cognitive and functional health are significantly positively associated with bridging, net of sociodemographic and life-course controls. The relationship between functional (kinesthetic) health and bridging appears to be partially mediated by network composition, as older adults who have poorer functional health also tend to have networks that are richer in strong ties. Several potential mediation mechanisms are discussed. Cognitive function remains significantly associated with bridging net of network composition, suggesting that the inherent challenges of maintaining bridging positions may be more difficult to cope with for those who have cognitive impairments than for those who have functional impairments such as limited mobility. An alternative explanation is that cognitively impaired individuals have more difficulty recognizing (and thus strategically using) bridges in their networks. Theoretical implications and possibilities for future research are discussed.     

Adjustment of issue positions based on network strategies in an election campaign: A two-mode network autoregression model with cross-nested random effects

During election campaigns, political parties deliver statements on salient issues in the news media, which are called issue positions. This article conceptualizes issue positions as a valued and longitudinal two-mode network of parties by issues. The network is valued because parties pronounce pro or con positions on issues in more or less extreme ways. It is longitudinal because the media report new statements of parties on issues each new day.     

A model for the multiplex dynamics of two-mode and one-mode networks,with an application to employment preference,friendship, and advice

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency.     

Analyzing event stream dynamics in two-mode networks: An exploratory analysis of private communication in a question and answer community

Information about social networks can often be collected as event stream data. However, most methods in social network analysis are defined for static network snapshots or for panel data. We propose an actor oriented Markov process framework to analyze the structural dynamics in event streams. Estimated parameters are similar to what is known from exponential random graph models or stochastic actor oriented models as implemented in SIENA. We apply the methodology on a question and answer web community and show how the relevance of different kinds of one- and two-mode network structures can be tested using a new software.     

Chronic illness and social network bridging in later life

Chronic disease has profound impacts on the structural features of individuals’ interpersonal connections such as bridging — ties to people who are otherwise poorly connected to each other. Prior research has documented competing arguments regarding the benefits of network bridging, but less is known about how chronic illness influences bridging and its underlying mechanisms. Using data on 1555 older adults from the National Social Life, Health, and Aging Project (NSHAP), I find that older adults diagnosed with chronic illness tend to have lower bridging potential in their networks, particularly between kin and non-kin members. They also report more frequent interactions with close ties but fewer neighbors, friends, and colleagues in their networks, which mediates the association between chronic illness and social network bridging. These findings illuminate both direct and indirect pathways through which chronic illness affects network bridging and highlight the context-specific implications for social networks in later life.     

Measuring knowledge and experience in two mode temporal networks

Two mode social network data consisting of actors attending events is a common type of social network data. For these kinds of data it is also common to have additional information about the timing or sequence of the events. We call data of this type two-mode temporal data. We explore the idea that actors attending events gain information from the event in two ways. Firstly the event itself may provide information or training; secondly, as co-attendees interact, they may pass on skills or information they have gleaned from other events. We propose a method of measuring these gains and demonstrate its usefulness using the classic Southern Women Data and a covert network dataset.     

Enhancing community capacity: Roles of perceived bonding and bridging social capital and public relations in community building

This study examined whether two types of perceived social capital – bonding and bridging – can affect individuals’ belief in community capacity in the context of a corporate community relations program to develop rural areas in South Korea. The results of the study's Web survey showed that perceived community capacity to resolve problems was significantly affected by their perception of both bonding and bridging social capital. The findings suggest that social capital serves as a mechanism that can foster community capacity through norms of interaction, reciprocity, and trust as aspects of civil society.     

Social network and family business: Uncovering hybrid family firms

What does it mean for a private enterprise in China to be embedded in a family? Our purpose here is twofold: (1) use social network analysis to describe what it means for a firm to be embedded in a family, (2) reveal from the application a new kind of firm, not family, yet akin to family. Armed with data on a large probability sample of private enterprises — a third of which meet ownership and employment criteria of being family businesses — we uncover a category of “hybrid family firms” that look modern in the style of firms that exclude family, but operate socially in ways similar to family firms. Our conclusion from summary statistics on the sample is that there are no differences in average performance level or network advantage for the three categories of businesses: family firms, hybrid family firms, and family-excluded firms. The fact that CEOs of family firms and hybrid family firms more often turn to family as key business contacts is a fact about network composition that raises no question about network mechanisms. Whether the CEO turns to more or fewer family contacts, government help is more likely with stronger political connections, and business success and survival are more likely with a large, open network. That said, the look-modern, act-traditional hybrid family firms stand alone in prospering with a CEO embedded in a closed business network. Recognition of hybrid family firms adds to the literature’s illustrations of social network analysis used to distinguish types of businesses and business people, and extends the population of organizations within which governance and strategy are likely to be better understood when viewed through a family logic.     

The Network Autocorrelation Model using Two-mode Data: Affiliation Exposure and Potential Bias in the Autocorrelation Parameter

The network autocorrelation model has been a workhorse for modeling network influences on individual behavior. The standard network approaches to mapping social influence using network measures, however, are limited to specifying an influence weight matrix (W) based on a single mode network. Additionally, it has been demonstrated that the estimate of the autocorrelation parameter ρ of the network effect tends to be negatively biased as the density in W matrix increases. The current study introduces a two-mode version of the network autocorrelation model. We then conduct simulations to examine conditions under which bias might exist. We show that the estimate for the affiliation autocorrelation parameter (ρ) tends to be negatively biased as density increases, as in the one-mode case. Inclusion of the diagonal of W, the count of the number of events participated in, as one of the variables in the regression model helps to attenuate such bias, however. We discuss the implications of these results.     

Why reputation is not always beneficial: Tolerance and opportunism in business networks

Many researchers in economics as well as sociology have stressed the important role of business networks for cooperation, trust, and performance. This claim is based on solid theoretical arguments as well as empirical findings. However, neither theory nor the selective empirical results support the view that networks are always beneficial for economic transactions. This paper begins with an observation that for the purchase of IT products, network embeddedness leads to even more problems for the customer. In order to explain this effect, possible reasons for this phenomenon are discussed using theory as well as empirics. The most promising explanation for this special case is the effect of uncertainty and incomplete information ex post. In order to reduce this uncertainty, the buyer forms beliefs on the basis of the opinions existing in a shared network or group. However, if the network members have the same problem of uncertainty, suppliers have an incentive to reduce their performance because such behavior will not be detected and sanctioned. An analysis of the customer's tolerance to a supplier's behavior in business transactions yields support for this argument. Even if problems in a transaction are kept constant, customers give suppliers more reputational credit if they share a common network.     

Assessing harmfulness and vulnerability in global bipartite networks of terrorist-target relationships

In this paper we leverage a massive attack-focused terrorist database and we design a dynamic bipartite network analysis to examine the structural evolution of terrorists-targets relationships. We introduce two novel measures to jointly assess harmfulness and vulnerability of terrorist and target groups, both at local and global level. Statistical validation using null models provides evidence that the information contained in these measures is new and not included in other variables, thus emphasizing the usefulness of these topological indicators. Finally, a policy-support experiment designed as network dismantling-like drill is proposed to assess the effects of potential attack preventive strategies.     

Ethnic segregation of friendship networks in school: Testing a rational-choice argument of differences in ethnic homophily between classroom- and grade-level networks

Adolescents’ school-based friendship networks tend to be segregated along ethnic lines. But few studies have examined whether variation in network boundaries affects the degree of ethnic friendship segregation. We use rational-choice theory to argue that ethnic homophily is more pronounced for friendships between classrooms than for those within classrooms. We empirically test this hypothesis using two-wave German panel data (N = 1258) and stochastic actor-oriented models (RSiena). In line with our theoretical argument, we find that the tendency to form same-ethnic friendships is indeed stronger at the grade level, which translates into stronger ethnic segregation in friendship networks at the grade level than at the classroom level. Implications for research on ethnic segregation in school-based friendship networks are discussed.     

Neoliberal co-optation and authoritarian renewal: social entrepreneurship networks in Jordan and Morocco

ABSTRACT

This paper analyzes social entrepreneurship networks (SENs) – composed of social entrepreneurs, business and political elites, and international actors – in Jordan and Morocco and how they foster processes of authoritarian renewal through neoliberal forms of co-optation. I argue that these new neoliberal networks and pre-existing patterns of social interaction complement each other, fostering linkages between well-established elites and hand-picked social entrepreneurs as well as societal groups. The two case studies illustrate different trajectories of the development of SENs and their embeddedness in the respective political, social and economic contexts. Importantly, such trajectories indicate a similar direction of travel: social entrepreneurship, rather than acting as a driver of progressive change, has been aligned with the authoritarian regimes and cements neoliberalism as a mode of governance. This mutation of neoliberal tactics towards more inclusionary and consensual patterns seeks to ensure the survival of both neoliberalism and of authoritarian governance. Thus, the article brings to light repertoires of authoritarian neoliberalism that have hitherto been under-studied. Moreover, it offers a critical perspective on social entrepreneurship as an increasingly popular phenomenon that, in academia and beyond, has all too often been approached from an uncritical and apolitical perspective.     

Echo chambers and social mediators in public advocacy issue networks

The growing trend of politically motivated consumer boycotts and buycotts on social media not only impacts a company’s financial bottom line, but more fundamentally disrupts relationships between the firm and its publics, the cornerstone of public relations (Ferguson, 1984; Sommerfeldt, & Kent, 2015). On a broader level, such politically motivated advocacy is a critical facet of civil society with important implications on the societal role of public relations (Taylor, 2010). In light of the significance of politically motivated consumer advocacy to public relations, a multi-phase, exploratory study was conducted. Study 1 applies content analysis and social network analysis to examine how different interactive mechanisms on social media—retweet, mention, and reply—may affect communication within and between communities of different ideological views surrounding the boycott and buycott issues. Study 2 further explores the challenges and opportunities of fostering exchange of diverse viewpoints by identifying new social mediators—the “echoers” who propel information flow among in-group members, and the “bridgers” who initiate communication with political out-group members—and assess the key network characteristics of these social mediators. The findings of these two studies advance public relations theories on networks, intergroup communication, and civil society by illustrating how social media structure and social mediators shape the networked public discourse to facilitate or inhibit conversations between publics of different ideological orientations.     

Triadic configurations in limited choice sociometric networks: Empirical and theoretical results

Previous research demonstrated that information contained in triad censuses from heterogeneous collections of social networks occupies a high dimensional space. Regions of this space, and locations of triad censuses within it, are largely defined by lower order network properties: network density and dyad distributions [Faust, K., 2006. Comparing social networks: size, density, and local structure. Metodološki Zvezki (Advances in Methodology and Statistics) 3 (2), 185–216; Faust, K., 2007. Very local structure in social networks. Sociological Methodology 37, 209–256]. The current paper extends comparative work on triad censuses by addressing three related issues. First, it determines and interprets the space occupied by triad censuses for 128 friendship networks gathered using a limited choice sociometric protocol. Second, it constructs a theoretical space for triad censuses expected given lower order graph properties and examines the dimensionality and shape of this space. Third, it brings together these lines of investigation to determine where the empirical triad censuses reside within the theoretical space. Results show that the empirical triad censuses are almost perfectly represented in one dimension (explaining 99% of the data) and that network density explains over 96% of the variance in locations on this dimension. In contrast, the theoretical space for triad censuses is at least four-dimensional, with distinctive regions defined by network density and dyad distributions. Within this theoretical space, the empirical triad censuses occupy a restricted region that closely tracks triad censuses expected given network density. Results differ markedly from prior findings that the space occupied by triad censuses from heterogeneous social networks is of high dimensionality. Results also reinforce observations about constraints that network size and density place on graph level indices.     

Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects models

Social network data often involve transitivity, homophily on observed attributes, community structure, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we develop Bayesian inference for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets: liking between monks and coreaderships between Slovenian publications. We also apply it to two simulated network datasets with very different network structure but the same highly skewed degree sequence generated from a preferential attachment process. One has transitivity and community structure while the other does not. Models based solely on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but the latent cluster random effects model does.     

In transit: Changing social networks of sub-Saharan African migrants in Turkey and Greece

Research on the role of social networks in human migration has mainly relied on single snapshots in time. This paper focuses on the changes in composition and usage of the transnational networks of migrants and why these changes occur. It is based on ethnography and network analysis with forty sub-Saharan African migrants in two transit contexts: Turkey and Greece, over a 17-month period. Findings show that relationship preferences, resources and communication infrastructures constitute an individual opportunity infrastructure affecting how critical events produce network changes. This process is ongoing through the continued experience of critical events, suggesting that the role of networks fluctuates over time.     

A puzzle concerning triads in social networks: Graph constraints and the triad census

Evidence from many sources shows that triadic tendencies are important structural features of social networks (e.g. transitivity or triadic closure) and triadic configurations are the basis for both theoretical claims and substantive outcomes (e.g. strength of weak ties, tie stability, or trust). A contrasting line of research demonstrates that triads in empirical social networks are well predicted by lower order graph features (density and dyads), accounting for around 90% of the variability in triad distributions when comparing different social networks (Faust, 2006, 2007, 2008). These two sets of results present a puzzle: how can substantial triadic tendencies occur when triads in empirical social networks are largely explained by lower order graph features? This paper provides insight into the puzzle by considering constraints that lower order graph features place on the triad census. Taking a comparative perspective, it shows that triad censuses from 159 social networks of diverse species and social relations are largely explained by their lower order graph features (the dyad census) through formal constraints that force triads to occur in narrow range of configurations. Nevertheless, within these constraints, a majority of networks exhibit significant triadic patterning by departing from expectation.