The influence of secrecy on the communication structure of covert networks

In order to be able to devise successful strategies for destabilizing covert organizations it is vital to recognize and understand their structural properties. Every covert organization faces the constant dilemma of staying secret and ensuring the necessary coordination between its members. Using elements from multi-objective optimization and bargaining game theory we analyze which communication structures are optimal in the sense of providing a balanced tradeoff between secrecy and operational efficiency. For several different secrecy and information scenarios this tradeoff is analyzed considering the set of connected graphs of given order as possible communication structures. Assuming uniform exposure probability of individuals in the network we show that the optimal communication structure corresponds to either a network with a central individual (the star graph) or an all-to-all network (the complete graph) depending on the link detection probability, which is the probability that communication between individuals will be detected. If the probability that an individual is exposed as member of the network depends on the information hierarchy determined by the structure of the graph, the optimal communication structure corresponds to a reinforced ring or wheel graph in case of an information measure based on average performance. In worst case performance with respect to information it can be seen that windmill wing graphs approximate optimal structures. Finally we give an example how optimal structures change when considering a non-balanced tradeoff between secrecy and operational efficiency.     

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.     

Integrated or Disconnected? Examining Formal and Informal Networks in a Merged Nonprofit Organization

This article introduces nonprofit researchers and practitioners to a social network analytical technique for assessing internal staff relationships after a merger. We studied a case of a nonprofit merger, investigating its formal and informal intraorganizational networks to see which parts integrated and which remained separate operationally. We discovered a prior‐organizational‐affiliation‐based homophily within the merged organization: most interpersonal relationships existing within these networks remained among the employees who worked together prior to the merger. However, the informal and expressive networks of mentoring, friendship, and socioemotional support were even more disconnected than the formal and instrumental networks of work relationships and problem solving. We highlight the role of a mentoring network in bridging formal and informal networks in a merged organization.     

Basic notions for the analysis of large two-mode networks

Many large real-world networks actually have a two-mode nature: their nodes may be separated into two classes, the links being between nodes of different classes only. Despite this, and despite the fact that many ad hoc tools have been designed for the study of special cases, very few exist to analyse (describe, extract relevant information) such networks in a systematic way. We propose here an extension of the most basic notions used nowadays to analyse large one-mode networks (the classical case) to the two-mode case. To achieve this, we introduce a set of simple statistics, which we discuss by comparing their values on a representative set of real-world networks and on their random versions. This makes it possible to evaluate their relevance in capturing properties of interest in two-mode networks.     

Logit Models for Affiliation Networks

Once confined to networks in which dyads could be reasonably assumed to be independent, the statistical analysis of network data has blossomed in recent years. New modeling and estimation strategies have made it possible to propose and evaluate very complex structures of dependency between and among ties in social networks. These advances have focused exclusively on one-mode networks—that is, networks of direct ties between actors. We generalize these models to affiliation networks, networks in which actors are tied to each other only indirectly through belonging to some group or event. We formulate models that allow us to study the (log) odds of an actor's belonging to an event (or an event including an actor) as a function of properties of the two-mode network of actors' memberships in events. We also provide illustrative analysis of some classic data sets on affiliation networks.     

k-means-based algorithm for blockmodeling linked networks

The paper presents a k-means-based algorithm for blockmodeling linked networks where linked networks are defined as a collection of one-mode and two-mode networks in which units from different one-mode networks are connected through two-mode networks. The reason for this is that a faster algorithm is needed for blockmodeling linked networks that can better scale to larger networks. Examples of linked networks include multilevel networks, dynamic networks, dynamic multilevel networks, and meta-networks. Generalized blockmodeling has been developed for linked/multilevel networks, yet the generalized blockmodeling approach is too slow for analyzing larger networks. Therefore, the flexibility of generalized blockmodeling is sacrificed for the speed of k-means-based approaches, thus allowing the analysis of larger networks. The presented algorithm is based on the two-mode k-means (or KL-means) algorithm for two-mode networks or matrices. As a side product, an algorithm for one-mode blockmodeling of one-mode networks is presented. The algorithm’s use on a dynamic multilevel network with more than 400 units is presented. A situation study is also conducted which shows that k-means based algorithms are superior to relocation algorithm-based methods for larger networks (e.g. larger than 800 units) and never much worse.     

Centrality in affiliation networks

This paper discusses the conceptualization, measurement, and interpretation of centrality in affiliation networks. Although centrality is a well-studied topic in social network analysis, and is one of the most widely used properties for studying affiliation networks, virtually all discussions of centrality and centralization have concerned themselves with one-mode networks. Bonacich's work on simultaneous group and individual centralities is a notable exception (Social Networks, 1991, 13, 155–168). I begin by outlining the distinctive features of affiliation networks and describe four motivations for centrality indices in affiliation networks. I then consider properties of some existing centrality indices for affiliation networks, including the relationship between centralities for actors and events in these networks, and present a new conceptualization of centrality that builds on the formal properties of affiliation networks and captures important theoretical insights about the positions of actors and events in these networks. These centralities are then illustrated on Galaskiewicz's data on club and board memberships of a sample of corporate executive officers (Social Organization of an Urban Grants Economy. New York: Academic Press, 1985). The conclusion to this paper discusses strengths and weaknesses of centrality indices when applied to affiliation networks.     

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.     

Betweenness computation in the single graph representation of hypergraphs

Many real-world social networks are hypergraphs because they either explicitly support membership in groups or implicitly include communities. We present the HyperBC algorithm that exactly computes betweenness centrality (or BC) in hypergraphs. The forward phase of HyperBC and the backpropagation phase are specifically tailored for BC computation on hypergraphs. In addition, we present an efficient method for pruning networks through the notion of “non-bridging” vertices. We experimentally evaluate our algorithm on a variety of real and artificial networks and show that it significantly speeds up the computation of BC on both real and artificial hypergraphs, while at the same time, being very memory efficient.     

Managing Multisite Nonprofits

Multisite nonprofit systems are organized in a variety of ways, ranging from central control to local control. Regardless of where a system falls along this organizational continuum, inevitable tensions emerge in the relationship between headquarters and the local organization. The purpose of this article is to understand the causes of these tensions and to offer management action that, regardless of the organizational structure, leads to greater system cohesion. Our exploration was facilitated by intense field research at five multisite systems: Outward Bound USA, Planned Parenthood, Habitat for Humanity, SOS Kinderdorf, and The Nature Conservancy. Our investigation suggests that multisite system behavior may be mapped on two dimensions—one that exerts forces toward unit autonomy and the other influencing the degree of organizational affiliation. These forces are associated with a host of organizational functions that are the traditional domains of management to influence and shape and thereby enable a multisite nonprofit to simultaneously optimize the benefits of organizational affiliation and unit autonomy.     

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.     

Transnational Movement Innovation and Collaboration: Analysis of World Social Forum Networks

In this article we first trace the ideological development and collective framing of the World Social Forum (WSF) as a non-hierarchical gathering for collaboration and networking within the global justice movement. We then analyze the consequences of organizational design, thematic resonance, and technological innovations implemented to produce more open and horizontal collaboration. We do this by conducting two-mode network analysis of organizations that facilitated sessions and workshops during two separate meetings (2003 and 2005) of the WSF in Porto Alegre, Brazil. Our findings indicate that organizational affiliations were less hierarchical in 2005, but we uncover mixed results from analyzing patterns of interaction produced by individual organizations and groups of organizations. Finally, we discuss the implications of such macro-level innovations on the dynamics of multi-organizational fields (collaboration, coalition building, and thematic resonance) and the contributions of such an approach to the study of transnational organizational networks.     

Partitioning large signed two-mode networks: Problems and prospects

While a substantial amount of attention within social network analysis (SNA) has been given to the study of one-mode networks, there is an increasing consideration of two-mode networks. Recent research on signed networks resulted in the relaxed structural balance (RSB) approach and its subsequent extension to signed two-mode networks involving social actors and social objects. We extend this approach to large signed two-mode networks, and address the methodological issues that arise. We develop tools to partition these types of networks and compare them with other approaches using a recently collected dataset of United Nations General Assembly roll call votes. Although our primary purpose is methodological, we take the first step towards bridging Heider's structural balance theory with recent theorizing in international relations on soft balancing of power processes.     

A sexual affiliation network of swingers,heterosexuals practicing risk behaviours that potentiate the spread of sexually transmitted infections: A two-mode approach

Using the example of the sexual affiliation networks of swingers, this paper examines how the analysis of sexual affiliation networks can contribute to the development of sexually transmitted infection (STI) prevention strategies. Two-mode network methodology and ERGMs are applied to describe the structural composition of the affiliation network and analyse attribute effects. Swingers were found to recruit their sex partners through one large, moderately cohesive network component. Swingers who used drugs or had a longer history of swinging tended to frequent websites instead of clubs. This study confirms the relevance of studying sexual affiliation networks and its additional value for STI epidemiology.     

Network stability in organizational flux: The case of in-house management consulting

This article explores the effects of organizational flux on the statics of interpersonal knowledge exchange structures. In our empirical case, organizational flux refers to high rates of personnel turnover, temporary project work, constant recombination of team memberships, and short-term collaboration. Network statics refers to the balance between forces composing and decomposing a network. Set in continuously changing organizational compositions of an in-house management-consulting unit, our study offers insights into the relationship between organizational characteristics and informal networks between experts. Against conventional intuition, we find a dense and stable structure of knowledge exchange. Furthermore, we elaborate on the two concepts of organizational flux and network statics, by comparing the observed structures with theoretical (random graphs) and empirical references (other empirical cases), and by using ERG models to account for different factors of organization, social balance, and individual attributes.     

Structural holes and bridging in two-mode networks

Social networks are often structured in such a way that there are gaps, or “structural holes,” between regions. Some actors are in the position to bridge or span these gaps, giving rise to individual advantages relating to brokerage, gatekeeping, access to non-redundant contacts, and control over network flows. The most widely used measures of a given actor’s bridging potential gauge the extent to which that actor is directly connected to others who are otherwise not well connected to each other. Unfortunately, the measures that have been developed to identify structural holes cannot be adapted directly to two-mode networks, like individual-to-organization networks. In two-mode networks, direct contacts cannot be directly connected to each other by definition, making the calculation of redundancy, effective size, and constraint impossible with conventional one-mode methods. We therefore describe a new framework for the measurement of bridging in two-mode networks that hinges on the mathematical concept of the intersection of sets. An actor in a given node class (“ego”) has bridging potential to the extent that s/he is connected to actors in the opposite node class that have unique profiles of connections to actors in ego’s own node class. We review the relevant literature pertaining to structural holes in two-mode networks, and we compare our primary bridging measure (effective size) to measures of bridging that result when using one-mode projections of two-mode data. We demonstrate the results of applying our approach to empirical data on the organizational affiliations of elites in a large U.S. city.     

A graph database framework for covert network analysis: An application to the Islamic State network in Europe

This paper proposes a new framework, based on graph database theory, for encoding complex data on covert networks, mapping their structure, and conducting a sensitivity analysis. The framework is then applied to reconstruct the terrorist network of the 2015–2016 attacks in Paris and Brussels, and related plots in Europe by the Islamic State group. The resulting network was found to be qualitatively different from the ideologically-related Al-Qaeda network, having a lower secrecy and a lower mean degree, under different network-generating assumptions.     

Confidentiality,power relations and evaluation of potential harm in the study of the personal and organizational networks of travel agents in Moscow

Network research in organizational contexts faces ethical challenges related to revealing the identity of participants, managing power relations, and managing the interests and potential harms of the different stakeholders. In this article, we review the ethical issues associated with the investigation of the personal and organizational networks of travel agents in Moscow. In our case study, we interviewed 32 tourism agents from Moscow and its region, obtaining information on 45 people with whom they have regular relation as part of their work; and relational data, with a 2-mode matrix, on 15 organizations with which the agency could be linked in the Russian-Andalusian tourism market. Our results highlight the utility of presenting the information of personal networks in an aggregate manner. It also demonstrates the value of cultural adaptation strategies and adjustment to the characteristics of the community. Moreover, the central role of power relations in organizations, within a cultural context with a greater distance to authority was also found.