Suchergebnisse

AbstractMetric graph properties lie in the heart of the analysis of complex networks, while in this paper we study their convexity through mathematical definition of a convex subgraph. A subgraph is convex if every geodesic path between the nodes of the subgraph lies entirely within the subgraph. According to our perception of convexity, convex network is such in which every connected subset of nodes induces a convex subgraph. We show that convexity is an inherent property of many networks that is not present in a random graph. Most convex are spatial infrastructure networks and social collaboration graphs due to their tree-like or clique-like structure, whereas the food web is the only network studied that is truly non-convex. Core–periphery networks are regionally convex as they can be divided into a non-convex core surrounded by a convex periphery. Random graphs, however, are only locally convex meaning that any connected subgraph of size smaller than the average geodesic distance between the nodes is almost certainly convex. We present different measures of network convexity and discuss its applications in the study of networks.

Ethnographic studies have hitherto focused on relationships among mobile actors, groups and how inter-ethnic relations are shaped by technologies and online information exchanges. However, little research has included the effects of virtual networks in relation to intra-ethnic structures. Facebook, as a media environment, facilitates 'doing family' across distance within transnational families. These routines shape intergroup solidarity through geographic distance by transmitting a selection of inter-ethnic references. What causes people to avoid inter-ethnic references on their Facebook timelines that are controversial, through self-censorship? And what are the social impacts of those choices – if any? How do these transnational socialisation practices ensure solidarity among Roma across borders? These are the questions answered in this paper based on offline and online ethnography of Roma migrant communities. The paper claims that although many coping strategies were learned from other ethnic minorities in the UK, stereotyped messages transmitted a selective narrative about other ethnic groups back to the participants' countries of origin to uphold ethnicity-based social assurances explained as instruments of ethnic solidarity. In short, the potential liberating power of virtual transnationalism was rather limited, while its potential to help reproduce social asymmetries was more apparent.

AbstractWe present a statistical framework for generating predicted dynamic networks based on the observed evolution of social relationships in a population. The framework includes a novel and flexible procedure to sample dynamic networks given a probability distribution on evolving network properties; it permits the use of a broad class of approaches to model trends, seasonal variability, uncertainty, and changes in population composition. Current methods do not account for the variability in the observed historical networks when predicting the network structure; the proposed method provides a principled approach to incorporate uncertainty in prediction. This advance aids in the designing of network-based interventions, as development of such interventions often requires prediction of the network structure in the presence and absence of the intervention. Two simulation studies are conducted to demonstrate the usefulness of generating predicted networks when designing network-based interventions. The framework is also illustrated by investigating results of potential interventions on bill passage rates using a dynamic network that represents the sponsor/co-sponsor relationships among senators derived from bills introduced in the U.S. Senate from 2003 to 2016.