Recent studies uncovered important core/periphery network structures characterizing complex sets of cooperative and competitive interactions between network nodes, be they proteins, cells, species or humans. Better characterization of the structure, dynamics and function of core/periphery networks is a key step of our understanding cellular functions, species adaptation, social and market changes. Here we summarize the current knowledge of the structure and dynamics of "traditional" core/periphery networks, rich-clubs, nested, bowtie and onion networks. Comparing core/periphery structures with network modules, we discriminate between global and local cores. The core/periphery network organization lies in the middle of several extreme properties, such as random/condensed structures, clique/star configurations, network symmetry/asymmetry, network assortativity/disassortativity, as well as network hierarchy/anti-hierarchy. These properties of high complexity together with the large degeneracy of core pathways ensuring cooperation and providing multiple options of network flow re-channelling greatly contribute to the high robustness of complex systems. Core processes enable a coordinated response to various stimuli, decrease noise, and evolve slowly. The integrative function of network cores is an important step in the development of a large variety of complex organisms and organizations. In addition to these important features and several decades of research interest, studies on core/periphery networks still have a number of unexplored areas.
In this study, using the network approach, we analyzed the urban public transportation systems of 5 Hungarian cities. We performed a comprehensive network analysis of the systems with the main goal of identifying significant similarities and differences of the transportation networks of these cities. Although previous studies often investigated unweighted networks, one novelty of our study is to consider directed and weighted links, where the weights represent the capacities of the vehicles (bus, tram, trolleybus) in the morning peak hours. In particular, we calculated descriptors of global network characteristic and various centrality measures of the network nodes in both the weighted case and unweighted case. By comparing the results obtained for the different cities, we get a highly detailed picture of the differences in the organization of the public transport, which may due to historical and geographical factors. Also, by comparing the results obtained from the weighted and unweighted approaches, we can identify which are the most sensitive routes and stations of the network pointing out some organizational inconsistencies of the transportation system.
We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Rand index and of the adjusted Wallace index respectively. The detection of cores is highly precise although the accuracy of the methodology can be limited in some cases.
In this paper, we investigate special types of Maker-Breaker games defined on graphs. We restrict Maker's possible moves that resembles the way that was introduced by Espig, Frieze, Krivelevich and Pedgen [9]. Here, we require that the subgraph induced by Maker's edges must be connected throughout the game. Besides the normal play, we examine the biased and accelerated versions of these games.
Two popular and widely used webpage ranking algorithms are PageRank and HITS. We considered the 2009 Szeged Wine Fest data and another reliable data set of wines from the famous region Villány, and, on basis of each data set, constructed a directed and weighted bipartite graph of wine tasters and wines. We applied an extended version of PageRank and HITS, the Co-HITS algorithm to wine tasting graph in order to rank tasters according to their ability and professional skill. The results of our technique were compared to other simple statistical methods. In general we observed that our ranking method performed better: it can filter out incompetent tasters, who, for example, gave the average score of some other tasters for the wines she or he tasted. Furthermore, our method gives a clearer picture about the competence of wine tasters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.