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The paper provides an overview of the global research on graduate education. The study applied a combination of a bibliometric and social network analysis methods to bibliographic data from Thompson Reuters' Web of Science. More specifically, a keyword search approach was used to retrieve 2,454 articles on graduate education from 1996 until 2020. The set was processed with the VantagePoint software. The paper reports the findings in the form of lists of top scholars, research centres, and countries contributing to research on graduate education. The findings include similar lists of the key funding agencies, contributing disciplines and publication venues, as well as maps representing collaborative activity in the field between institutions, and countries. Finally, the frequency of utilisation of groups of author-supplied keywords is analysed to determine the basic thematic structure of the research on the topic. The originality of the paper consists in the fact that it represents the first attempt to map the landscape of research on graduate education using bibliographic data. It can be used to supplement the results of literature reviews on the topic, which apply a more in-depth content analysis-based approaches to a limited number of papers to determine the thematic structure of the field.

This paper seeks to bridge the gap between archival text analysis and network analysis by applying network clustering methods to analyze the coverage of Bulgaria in 123 issues of the newspaper Osservatore Romano published between January and May 1877. Utilizing optical character recognition and generalized homogeneity blockmodeling, the study constructs networks of relevant keywords. Those including the sets Bulgaria and Russia are rather isomorphic and they largely overlap with those for Germany, Britain, and War. In structural terms, the blockmodel of the two networks exhibits a clear core-semiperiphery-periphery structure that reflects relations between concepts in the newpaper's coverage. The newspaper's lexical choices effectively delegitimised the Bulgarian national revival, highlighting the influence of the Holy See on the newspaper's editorial line. [ABSTRACT FROM AUTHOR]

The Russian-Ukrainian war, which broke out on February 24, 2022, resulted in several paradigm shifts in cyber warfare. One aspect of these changes is psychological operations. Russia and Ukraine have conducted extensive psychological operation campaigns to fulfil their war objectives, which have since been intense along modified intentions. This series of studies examines the impact of war-related fake news through various empirical research. In the first part of the paper, the authors examine the emergence of psychological operations and related terms in the international academic literature using network analysis methodology. In the second part of the paper, the authors use sentiment and network analysis to investigate the spread of different fake news. In the third study, the authors measure the attitudes toward the perception of the Hungarian Defence Forces from the perspective of the war in the neighbouring country. [ABSTRACT FROM AUTHOR]

Orienteering problem (OP) is a routing problem, where the aim is to generate a path through set of nodes, which would maximize total score and would not exceed the budget. In this paper, we present an extension of classic OP—Orienteering Problem with Functional Profits (OPFP), where the score of a specific point depends on its characteristics, position in the route, and other points in the route. For solving OPFP, we developed an open-source framework for solving orienteering problems, which utilizes four core components of OP in its modular architecture. Fully-written in Go programming language our framework can be extended for solving different types of tasks with different algorithms; this was demonstrated by implementation of two popular algorithms for OP solving—Ant Colony Optimization and Recursive Greedy Algorithm. Computational efficiency of the framework was shown through solving four well-known OP types: classic Orienteering Problem (OP), Orienteering Problem with Compulsory Vertices (OPCV), Orienteering Problem with Time Windows (OPTW), and Time Dependent Orienteering Problem (TDOP) along with OPFP. Experiments were conducted on a large multi-source dataset for Saint Petersburg, Russia, containing data from Instagram, TripAdvisor, Foursquare and official touristic website. Our framework is able to construct touristic paths for different OP types within few seconds using dataset with thousands of points of interest. [ABSTRACT FROM AUTHOR]

In August 2014, the Russian Federation imposed counter-sanctions against Western countries imposing restrictions against Russia following its aggression against Ukraine. It is worth examining to what extent the counter-sanctions have transformed the trade network between the countries. This study aims to show the impact of this embargo on apple import on the global trade network due to the Russian response to the Western countries' measures in 2014. We chose the methodology of network research to examine the changes in trade networks. We analyzed the apple trade network because this was one of the significant fields impacted by the trade restrictions and panic reactions from EU producers imposed on the sanction. This research shows that Russian import was also impacted negatively, but some third countries are quickly becoming the winners of the restrictions. Serbia and Azerbaijan were the clear winners of the sanctions. The research results show that network research methodology is suitable for examining the sanctions' effects. [ABSTRACT FROM AUTHOR]

The stereotype content model (SCM), originating in the United States and generalized across nearly 50 countries, has yet to address ethnic relations in one of the world's most influential nations. Russia and the United States are somewhat alike (large, powerful, immigrant-receiving), but differ in other ways relevant to intergroup images (culture, religions, ideology, and history). Russian ethnic stereotypes are understudied, but significant for theoretical breadth and practical politics. This research tested the SCM on ethnic stereotypes in a Russian sample (N = 1115). Study 1 (N = 438) produced an SCM map of the sixty most numerous domestic ethnic groups (both ethnic minorities and immigrants). Four clusters occupied the SCM warmth-by-competence space. Study 2 (N = 677) compared approaches to ethnic stereotypes in terms of status and competition, cultural distance, perceived region, and four intergroup threats. Using the same Study 1 groups, the Russian SCM map showed correlated warmth and competence, with few ambivalent stereotypes. As the SCM predicts, status predicted competence, and competition negatively predicted warmth. Beyond the SCM, status and property threat both were robust antecedents for both competence and warmth for all groups. Besides competition, cultural distance also negatively predicted warmth for all groups. The role of the other antecedents, as expected, varied from group to group. To examine relative impact, a network analysis demonstrated that status, competition, and property threat centrally influence many other variables in the networks. The SCM, along with antecedents from other models, describes Russian ethnic-group images. This research contributes: (1) a comparison of established approaches to ethnic stereotypes (from acculturation and intergroup relations) showing the stability of the main SCM predictions; (2) network structures of the multivariate dependencies of the considered variables; (3) systematically cataloged images of ethnic groups in Russia for further comparisons, illuminating the Russian historical, societal, and interethnic context. [ABSTRACT FROM AUTHOR]

Background: Anaplasma phagocytophilum is currently regarded as a single species. However, molecular studies indicate that it can be subdivided into ecotypes, each with distinct but overlapping transmission cycle. Here, we evaluate the interactions between and within clusters of haplotypes of the bacterium isolated from vertebrates and ticks, using phylogenetic and network-based methods. Methods: The presence of A. phagocytophilum DNA was determined in ticks and vertebrate tissue samples. A fragment of the groEl gene was amplified and sequenced from qPCR-positive lysates. Additional groEl sequences from ticks and vertebrate reservoirs were obtained from GenBank and through literature searches, resulting in a dataset consisting of 1623 A. phagocytophilum field isolates. Phylogenetic analyses were used to infer clusters of haplotypes and to assess phylogenetic clustering of A. phagocytophilum in vertebrates or ticks. Network-based methods were used to resolve host-vector interactions and their relative importance in the segregating communities of haplotypes. Results: Phylogenetic analyses resulted in 199 haplotypes within eight network-derived clusters, which were allocated to four ecotypes. The interactions of haplotypes between ticks, vertebrates and geographical origin, were visualized and quantified from networks. A high number of haplotypes were recorded in the tick Ixodes ricinus. Communities of A. phagocytophilum recorded from Korea, Japan, Far Eastern Russia, as well as those associated with rodents had no links with the larger set of isolates associated with I. ricinus, suggesting different evolutionary pressures. Rodents appeared to have a range of haplotypes associated with either Ixodes trianguliceps or Ixodes persulcatus and Ixodes pavlovskyi. Haplotypes found in rodents in Russia had low similarities with those recorded in rodents in other regions and shaped separate communities. Conclusions: The groEl gene fragment of A. phagocytophilum provides information about spatial segregation and associations of haplotypes to particular vector-host interactions. Further research is needed to understand the circulation of this bacterium in the gap between Europe and Asia before the overview of the speciation features of this bacterium is complete. Environmental traits may also play a role in the evolution of A. phagocytophilum in ecotypes through yet unknown relationships. [ABSTRACT FROM AUTHOR]

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Abstract: The economic transition from socialism in Russia has not resulted in the emergence of impersonal, rule‐based institutions. Instead, the natural demand for institutions that protect property rights has led to the emergence of alternative, inefficient institutions such as that of cronyism – the practice of appointing personal acquaintances of the political leader to key positions. A political leader not constrained by institutions appoints cronies, as competent subordinates are more prone to switching allegiance to a potential challenger. As competence makes a bigger difference in a rule‐based environment, such a leader has no interest in any institutional development. In a simple empirical exercise, using a dataset that covers the richest Russians, we find a positive and significant effect of direct connections to the personal circle of President Putin on the wealth of businessmen. The magnitude of the effect varies at different levels of rents available for redistribution and ‘network centrality of a businessman’: it is higher during the years of high oil prices, but is attenuated by the prominence of the businessman in the network. [ABSTRACT FROM AUTHOR]

Following Hausmann et al. (2011), we apply a network approach to measure the level of economic complexity and diversification opportunities of Russian regions. Using Russian and international export data, we find that the complexity of Russian regional economies varies substantially: relatively high in western and central regions, lower in southern and northern Russia and lowest in eastern regions. While Russian regions, on average, have poor diversification opportunities, regions can still diversify their exports by participating in international value-added chains or cooperating in developing group strategies. Our results are highly consistent with two well-established rankings of Russian regional R&D development based on numerous regional indicators, and imply that our network-based measure of complexity captures important features such as the level of regional R&D. [ABSTRACT FROM AUTHOR]

The conflict in Chechnya is characterized by a high degree of complexity. To capture this complexity, the authors produced an actors' network analysis drawing on one of the largest event databases today. The aim was to identify the main actors involved in the conflict, track down the most important conflictive and cooperative ties between actors, and compare the quality and intensity of interactions among actor groups. In total, 2,818 events reported between 2002 and 2005 were assigned forty-four actors categories. Measures of centrality and power and a combination of principal component and cluster analysis were used to produce graphs of the network. The authors found civilians to be the most important actors, closely followed by the Russian military, the Chechen fighters, and the Chechen government. The results are discussed in light of the current situation in Chechnya with reference to chances and limitations of the network approach with event data. [ABSTRACT FROM AUTHOR]

Following Hausmann et al. (2011), we apply a network approach to measure the level of economic complexity and diversification opportunities of Russian regions. Using Russian and international export data, we find that the complexity of Russian regional economies varies substantially: relatively high in western and central regions, lower in southern and northern Russia and lowest in eastern regions. While Russian regions, on average, have poor diversification opportunities, regions can still diversify their exports by participating in international value-added chains or cooperating in developing group strategies. Our results are highly consistent with two well-established rankings of Russian regional R&D development based on numerous regional indicators, and imply that our network-based measure of complexity captures important features such as the level of regional R&D. [ABSTRACT FROM AUTHOR]