Overcoming the liability of distance? An exploratory study of the associations between social networks, sense of community and spatial colocation

Purpose This study aims to examine the associations of social networks with the sense of community (SOC) construct and spatial colocation or having an office. The study site was an institute for health-care policy research formed in 2011 by bringing together scientists from more than 20 different university units. Only 30% of the scientists were had an office or physical presence at the institute. Therefore, the institute was an ideal site to examine whether SOC was correlated with different dimensions of network position – connectedness, reachability and brokerage – even when the authors account for the lack of spatial colocation for the off-site scientists. Design/methodology/approach A two-part (sociometric and workplace) internet survey instrument was administered in 2014 to the institute’s population of 411 individuals. The sociometric data were used to create an undirected interaction network and the following dependent variables (DVs) or network centralities: normalized degree to measure connectedness; average reciprocal distance to capture reachability; and normalized betweenness to proxy brokerage. Separate node-level network regressions were then run with random permutations (N = 10,000) and listwise deletion for each of the DVs with SOC and spatial colocation as the independent variables, and variables that controlled for gender, organizational affiliation and job category. Findings SOC and spatial colocation are both positively and significantly correlated with network connectedness and reachability. The results suggest that both SOC and spatial colocation have a larger impact on reachability than connectedness. However, neither SOC nor spatial colocation are significantly associated with network brokerage. Finally, the findings show that SOC and spatial colocation are more reliable predictors of network connectedness and reachability than are key individual- and unit-level control variables, specifically the individual’s sex, job category and organizational affiliation. The controls were not significantly associated with any of the three network centralities, namely, connectedness, reachability and brokerage. Originality/value This exploratory study used social network analysis and node-level network regressions to examine the associations from SOC and spatial colocation to dimensions of network position. SOC is positively and significantly associated with network connectedness and reachability, suggesting that SOC is an important consideration when individuals are disadvantaged from the absence of spatial colocation. The findings have implications for work in the context of the COVID-19 pandemic as they imply that interventions based on the SOC construct could potentially lessen the negative effects of remote work on workplace social networks due to factors such as the reduction of social contacts.

Entropy and Network Centralities as Intelligent Tools for the Investigation of Terrorist Organizations

In recent years, law enforcement authorities have increasingly used mathematical tools to support criminal investigations, such as those related to terrorism. In this work, two relevant questions are discussed: “How can the different roles of members of a terrorist organization be recognized?” and “are there early signs of impending terrorist acts?” These questions are addressed using the tools of entropy and network theory, more specifically centralities (degree, betweenness, clustering) and their entropies. These tools were applied to data (physical contacts) of four real terrorist networks from different countries. The different roles of the members are clearly recognized from the values of the selected centralities. An early sign of impending terrorist acts is the evolutionary pattern of the values of the entropies of the selected centralities. These results have been confirmed in all four terrorist networks. The conclusion is expected to be useful to law enforcement authorities to identify the roles of the members of terrorist organizations as the members with high centrality and to anticipate when a terrorist attack is imminent, by observing the evolution of the entropies of the centralities.

Analysing cultural networks in cross-border metropolitan regions. The case of the Upper Rhine region (Germany–Switzerland–France)

In the last few decades, cross-border metropolitan regions (CBMRs) have been examined through the lens of binary prevailing network analysis, with substantial focus being placed on economy, innovations, and governance. However, the analysis of cultural networks is underrepresented in these contexts, although several voices have enquired about new concepts and practices for measuring spatial cultural networks and social proximities. This study was concerned with measuring cultural networks, as one step towards obtaining a deeper understanding of CBMRs. When focusing on cultural networks in border studies, it is necessary to understand: 1) how spatio-cultural networks can be conceptualised and measured from an interdisciplinary perspective; and 2) how cultural networks influence cross-border relations. Some of the literature has identified culture as the complex interrelation of values, artefacts, and behaviours, which presents multiple difficulties for analysing culture, per se. To analyse the influence of cultural networks in cross-border areas, this work took the Upper Rhine (UR), between the nation states of Germany, France, and Switzerland, as a case study. In the literature, this region is mainly referred to as being one coherent, integrated CBMR that shares similar dominant values. However, with regard to border cultural networks and national identities, this is empirically questionable. The UR region was analysed using two datasets, one quantitative and one qualitative. The analytical framework was based on the interlocking network model (INM) developed by Taylor (2001), which measures network and city centralities. Some adaptations were made to the INM to specifically analyse cultural networks in cross-border regions, giving rise to an ‘extended’ INM (EINM). Firstly, it was found that, although well-established cultural interrelations were identifiable in the UR cross-border region, a negative national border effect exists, leading to an uneven integration of German, Swiss and French cities into the cultural networks. Secondly, there was a significant difference between the INM and EINM, in terms of the number of relations and network centralities that could be captured, which led to different conclusions.

The network boundary specification problem in the global and world city research: investigation of the reliability of empirical results from sampled networks

Despite the well-known dependence of vertex and network structural parameters on network boundary specification employed by researchers, there has so far been effectively no discussion of this methodological caveat in the global and world city literature. Given the reliance of empirical studies of urban networks on the sampling of underlying actors that form these networks by their interactions, we consider it of key importance to examine the dependence of network centralities of cities on network boundary specification. We consider three distinctive modelling approaches based on: (a) office networks, (b) ownership ties and (c) inter-organisational projects. Our results indicate that city network centralities obtained from sampled networks are highly consistent with those obtained from whole network analysis for samples featuring as little as 4% (office networks), 10% (ownership ties) and 25% (inter-organisational projects) of the underlying actors.

Homothetic Behavior of Betweenness Centralities: A Multiscale Alternative Approach to Relate Cities and Large Regional Structures

Regional configuration can reveal important aspects about city sustainability, as local-regional interactions shape the evolution and inner geography of urban settlements. However, modelling these large-scale structures remains a challenge, due to their sheer size as physical objects. Despite recent improvements in processing power and computing methods, extensive time periods are still required for ordinary microprocessors to model network centralities in road-graphs with high element counts, connectivity and topological depth. Generalization is often the chosen option to mitigate time-constraints of regional network complexity. Nevertheless, this can impact visual representation and model precision, especially when multiscale comparisons are desired. Tests using Normalized Angular Choice (NACH), a Space Syntax mathematical derivative of Betweenness Centrality, found recursive visual similitudes in centrality spatial distribution when modelling distinct scaled map sections of the same large regional network structure. Therefore, a sort of homothetic behavior is identified, since statistical analyses demonstrate that centrality values and distributions remain rather consistent throughout scales, even when considering edge effects. This paper summarizes these results and considers homotheties as an alternative to extensive network generalization. Hence, data maps can be constructed sooner and more accurately as “pieces of a puzzle”, since each individual lesser scale graph possesses a faster processing time.

Analyzing Promising Researchers Using Network Centralities of Co-authorship Networks from Academic Literature

We propose a new way of using the betweenness centrality measure with co-author networks from an academic literature database to evaluate young researchers. It is difficult to discover and evaluate promising young researchers with indexes based on the number of cited papers, such as the h-index to which published papers introduce a lag and whose impact only becomes apparent after they have been cited by other papers. We validated the effectiveness of the measure as an index for evaluating young researchers. Our investigation of 1.92 million publications in the biological sciences shows that Research Fellows with the Japan Society for the Promotion of Science (JSPS) have higher rankings and progress more quickly than other researchers. In addition, differences between JSPS Research Fellows and other researchers were observed at earlier stages using the proposed method than with the h-index and with centralities from literature published in the past 4 years. We expect that the proposed use of the betweenness centrality measure can be applied effectively to extract promising young researchers.