411 research outputs found

    The role of networks in labor markets

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    Networks of relationships play an important role in the social and economic operation of the labor market. Social connections have been shown to be crucial in influencing the transition and efficiency in the labor market because they can quickly spread information over large segments of society. In particular in “small world” networks everyone can connect to others through very few intermediaries and information can spread far and fast over such a small-world network. The first chapter of this dissertation starts with the formal elements of social network analysis and graph theory. It then provides an overview of the emerging literature on models of small worlds. Networks characterized by very small characteristic path lengths, yet high clustering coefficients, are said to exhibit the small-world phenomenon. Since interactions or links in the academic labor market are observed easier than other labor markets, the second chapter investigates the labor market for academic economists from a social network perspective. The sample includes the top two hundred economics departments in the world and provides a separate analysis of the subset pertaining to North America. The data indicates the stronger links between higher ranked universities than between the universities in the higher and lower ranked universities. The obvious pattern of interaction in the network is that the top-ranked grantors place their Ph.D. economists mostly in group ranked below them. The small-world properties of this network are examined in the third chapter. The data confirms the small-world phenomenon in the economics academic network. Any two ranked universities can be connected through approximately three links only. Although it is shown that there is inequality in the placement of Ph.D. students, there are many centers of connections in the network. However, most of the influential universities in terms of centrality of the network are not the ones influential in granting doctoral degrees

    How to choose the most appropriate centrality measure?

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    We propose a new method to select the most appropriate network centrality measure based on the user's opinion on how such a measure should work on a set of simple graphs. The method consists in: (1) forming a set F\cal F of candidate measures; (2) generating a sequence of sufficiently simple graphs that distinguish all measures in F\cal F on some pairs of nodes; (3) compiling a survey with questions on comparing the centrality of test nodes; (4) completing this survey, which provides a centrality measure consistent with all user responses. The developed algorithms make it possible to implement this approach for any finite set F\cal F of measures. This paper presents its realization for a set of 40 centrality measures. The proposed method called culling can be used for rapid analysis or combined with a normative approach by compiling a survey on the subset of measures that satisfy certain normative conditions (axioms). In the present study, the latter was done for the subsets determined by the Self-consistency or Bridge axioms.Comment: 26 pages, 1 table, 1 algorithm, 8 figure

    Asymmetric evolutionary games

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    Evolutionary game theory is a powerful framework for studying evolution in populations of interacting individuals. A common assumption in evolutionary game theory is that interactions are symmetric, which means that the players are distinguished by only their strategies. In nature, however, the microscopic interactions between players are nearly always asymmetric due to environmental effects, differing baseline characteristics, and other possible sources of heterogeneity. To model these phenomena, we introduce into evolutionary game theory two broad classes of asymmetric interactions: ecological and genotypic. Ecological asymmetry results from variation in the environments of the players, while genotypic asymmetry is a consequence of the players having differing baseline genotypes. We develop a theory of these forms of asymmetry for games in structured populations and use the classical social dilemmas, the Prisoner's Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric games reveal essential differences between models of genetic evolution based on reproduction and models of cultural evolution based on imitation that are not apparent in symmetric games.Comment: accepted for publication in PLOS Comp. Bio

    A Community Detection Method Towards Analysis of Xi Feng Parties in the Northern Song Dynasty

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    Intra-family links in the analysis of marital networks

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    Marriage networks, which represent the matrimonial connections between different families in a given historical and geographical milieu, rarely take into account one aspect of internal family dynamics, namely the existence of intra-family marriages. The inclusion of such marriages, represented in the graph by self-loops, is essential in order to compute more accurate measures of centrality. In this paper, we discuss various procedures for incorporating these links into the analysis, with the requirement that they be compatible with the use of already available social network analysis software. We then apply them to two historical marriage networks, one from the Republic of Venice and the other from Taiwan. By comparing centrality measures for the baseline and modified networks, we found that the most satisfactory of the proposed methods is the one that duplicates nodes of families with intra-family marriages and adds new edges that link these duplicated nodes to all the families to which the original node was connected. This procedure is computationally simple and conceptually sound, making it a useful tool for analysing marital networks.PID2020-115570GB-C22 (DemocratAI::UGR) Acceso abierto financiado por Universidad de Granada/CBU

    Graph Theory and Networks in Biology

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    In this paper, we present a survey of the use of graph theoretical techniques in Biology. In particular, we discuss recent work on identifying and modelling the structure of bio-molecular networks, as well as the application of centrality measures to interaction networks and research on the hierarchical structure of such networks and network motifs. Work on the link between structural network properties and dynamics is also described, with emphasis on synchronization and disease propagation.Comment: 52 pages, 5 figures, Survey Pape
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