Relating real and synthetic social networks through centrality measures

We perform here a comparative study on the behaviour of real and synthetic social networks with respect to a selection of nine centrality measures. Some of them are topology based (degree, closeness, betweenness), while others consider the relevance of the actors within the network (Katz, PageRank) or their ability to spread influence through it (Independent Cascade rank, Linear Threshold Rank). We run different experiments on synthetic social networks, with 1K, 10K, and 100K nodes, generated according to the Gaussian Random partition model, the stochastic block model, the LFR benchmark graph model and hyperbolic geometric graphs model. Some real social networks are also considered, with the aim of discovering how do they relate to the synthetic models in terms of centrality. Apart from usual statistical measures, we perform a correlation analysis between all the nine measures. Our results indicate that, in general, the correlation matrices of the different models scale nicely with size. Moreover, the correlation plots distinguish four categories that classify most of the real networks studied here. Those categories have a clear correspondence with particular configurations of the models for synthetic networks.M. Blesa and M. Serna acknowledge support by MICIN/AEI/10.13039/501100011033 under grant PID2020-112581GB-C21 (MOTION). M.E. Popa was funded by the Ministry of Education and Vocational Training (MEFP) with a student grant (Beca de colaboración, call 2020-2021)Peer ReviewedPostprint (published version

Co-authorship networks in Swiss political research

Co-authorship is an important indicator of scientific collaboration. Co-authorship networks are composed of sub-communities, and researchers can gain visibility by connecting these insulated subgroups. This article presents a comprehensive co-authorship network analysis of Swiss political science. Three levels are addressed: disciplinary cohesion and structure at large, communities, and the integrative capacity of individual researchers. The results suggest that collaboration exists across geographical and language borders even though different regions focus on complementary publication strategies. The subfield of public policy and administration has the highest integrative capacity. Co-authorship is a function of several factors, most importantly being in the same subfield. At the individual level, the analysis identifies researchers who belong to the “inner circle” of Swiss political science and who link different communities. In contrast to previous research, the analysis is based on the full set of publications of all political researchers employed in Switzerland in 2013, including past publications

Throughflow centrality is a global indicator of the functional importance of species in ecosystems

To better understand and manage complex systems like ecosystems it is critical to know the relative contribution of system components to system functioning. Ecologists and social scientists have described many ways that individuals can be important; This paper makes two key contributions to this research area. First, it shows that throughflow, the total energy-matter entering or exiting a system component, is a global indicator of the relative contribution of the component to the whole system activity. It is global because it includes the direct and indirect exchanges among community members. Further, throughflow is a special case of Hubbell status as defined in social science. This recognition effectively joins the concepts, enabling ecologists to use and build on the broader centrality research in network science. Second, I characterize the distribution of throughflow in 45 empirically-based trophic ecosystem models. Consistent with expectations, this analysis shows that a small fraction of the system components are responsible for the majority of the system activity. In 73% of the ecosystem models, 20% or less of the nodes generate 80% or more of the total system throughflow. Four or fewer dominant nodes are required to account for 50% of the total system activity. 121 of the 130 dominant nodes in the 45 ecosystem models could be classified as primary producers, dead organic matter, or bacteria. Thus, throughflow centrality indicates the rank power of the ecosystems components and shows the power concentration in the primary production and decomposition cycle. Although these results are specific to ecosystems, these techniques build on flow analysis based on economic input-output analysis. Therefore these results should be useful for ecosystem ecology, industrial ecology, the study of urban metabolism, as well as other domains using input-output analysis.Comment: 7 figures, 2 table

Community-based Immunization Strategies for Epidemic Control

Understanding the epidemic dynamics, and finding out efficient techniques to control it, is a challenging issue. A lot of research has been done on targeted immunization strategies, exploiting various global network topological properties. However, in practice, information about the global structure of the contact network may not be available. Therefore, immunization strategies that can deal with a limited knowledge of the network structure are required. In this paper, we propose targeted immunization strategies that require information only at the community level. Results of our investigations on the SIR epidemiological model, using a realistic synthetic benchmark with controlled community structure, show that the community structure plays an important role in the epidemic dynamics. An extensive comparative evaluation demonstrates that the proposed strategies are as efficient as the most influential global centrality based immunization strategies, despite the fact that they use a limited amount of information. Furthermore, they outperform alternative local strategies, which are agnostic about the network structure, and make decisions based on random walks.Comment: 6 pages, 7 figure

THE ROLE OF CROSS-CLASS ALLIANCES AND ELITES IN COORDINATED EMPLOYMENT RELATIONS IN DENMARK. CES Open Forum Series 2018-2019, September 4, 2018

Explanations for coordination between labor and capital in Northern Europe continue to cause debate among scholars of comparative political economy. On one hand, power resource scholars argue that strong trade unions promoting equality are necessary for coordination. On the other hand, employer-centered theories argue that employers are the primary actors in promoting coordination due to the comparative advantages stemming from coordination. To inform this debate, we study the case of Denmark by combining a unique database of 5.000 elite affiliations with 80 stakeholder interviews spanning a decade. We argue that trade union power resources are necessary for coordination. However, only when certain segments of labor can forge powerful alliances with key employers for the economy will coordination persist. The network analysis identifies a powerful cross-class alliance between trade unions and employer associations in manufacturing. Interviews with stakeholders show that coordination in industrial relations and related institutional spheres such as education and industrial policies serves this alliance’s interests in safeguarding international competitiveness of manufacturing. However, intra-class allegiances ensure that the alliance constantly has to consider the interests of outsider organizations