615 resultados para Eigenvector centrality
Resumo:
We extend the concept of eigenvector centrality to multiplex networks, and introduce several alternative parameters that quantify the importance of nodes in a multi-layered networked system, including the definition of vectorial-type centralities. In addition, we rigorously show that, under reasonable conditions, such centrality measures exist and are unique. Computer experiments and simulations demonstrate that the proposed measures provide substantially different results when applied to the same multiplex structure, and highlight the non-trivial relationships between the different measures of centrality introduced.
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We propose and discuss a new centrality index for urban street patterns represented as networks in geographical space. This centrality measure, that we call ranking-betweenness centrality, combines the idea behind the random-walk betweenness centrality measure and the idea of ranking the nodes of a network produced by an adapted PageRank algorithm. We initially use a PageRank algorithm in which we are able to transform some information of the network that we want to analyze into numerical values. Numerical values summarizing the information are associated to each of the nodes by means of a data matrix. After running the adapted PageRank algorithm, a ranking of the nodes is obtained, according to their importance in the network. This classification is the starting point for applying an algorithm based on the random-walk betweenness centrality. A detailed example of a real urban street network is discussed in order to understand the process to evaluate the ranking-betweenness centrality proposed, performing some comparisons with other classical centrality measures.
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Notre étude porte sur la manière dont les chercheurs universitaires junior et senior en sciences sociales au Québec établissent leurs réseaux de cosignataires et donnent une interprétation discursive à leurs activités de collaboration face à l'impact du changement institutionnel universitaire pendant la période 1990-2009. Plus spécifiquement, notre recherche s'intéresse à montrer que la création des réseaux et la collaboration scientifique par cosignature peuvent être identifiées comme des « ajustements professionnels » et se présenter aussi comme une ressource du capital social qui peut être mobilisé et qui peut produire des avantages aux chercheurs en accord avec leur statut junior ou senior. Il s’agit donc d’une recherche qui relève de la sociologie des sciences. Notre approche a été opérationnalisée à partir de l'étude de 15 membres d'un centre de recherche universitaire au Québec, et leur réseau de 447 cosignataires (y compris les chercheurs de l'étude), et à travers l'application de 7 entretiens auprès de chercheurs junior et senior du même centre. Dans le même plan opérationnel, depuis une perspective qualitative, la thèse permet d'identifier le sens discursif que les chercheurs fournissent à la collaboration et à la participation en réseaux de cosignatures. Ensuite, depuis l'analyse structurelle des réseaux, notre étude montre les connexions individuelles et leurs formes d'interprétation — spécialement la théorie des graphes et ses mesures de centralité (la centralité de degré, la centralité d’intermédiarité et la centralité de vecteur propre) — de même que l'homophilie par statut entre chercheurs. Enfin, depuis l'analyse statistique, elle montre la corrélation des périodes de l'étude et des attributs socioprofessionnels des chercheurs étudiés (sexe, statut universitaire, affiliation institutionnelle, discipline d’appartenance, pays, région du Canada et ville de travail). Notamment, les résultats de notre thèse montrent que chaque catégorie de chercheurs possède ses propres particularités structurelles et discursives en ce qui a trait à ses pratiques de collaboration en réseau, et vont confirmer que les chercheurs senior, plus que les chercheurs junior, grâce à leur capital social mobilisé, ont conservé et obtenu plus d'avantages de leur réseau de cosignataires afin de s'adapter au changement institutionnel et mieux gérer leur travail de collaboration destiné à l’espace international, mais surtout à l'espace local.
Resumo:
A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.
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This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.
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A character network represents relations between characters from a text; the relations are based on text proximity, shared scenes/events, quoted speech, etc. Our project sketches a theoretical framework for character network analysis, bringing together narratology, both close and distant reading approaches, and social network analysis. It is in line with recent attempts to automatise the extraction of literary social networks (Elson, 2012; Sack, 2013) and other studies stressing the importance of character- systems (Woloch, 2003; Moretti, 2011). The method we use to build the network is direct and simple. First, we extract co-occurrences from a book index, without the need for text analysis. We then describe the narrative roles of the characters, which we deduce from their respective positions in the network, i.e. the discourse. As a case study, we use the autobiographical novel Les Confessions by Jean-Jacques Rousseau. We start by identifying co-occurrences of characters in the book index of our edition (Slatkine, 2012). Subsequently, we compute four types of centrality: degree, closeness, betweenness, eigenvector. We then use these measures to propose a typology of narrative roles for the characters. We show that the two parts of Les Confessions, written years apart, are structured around mirroring central figures that bear similar centrality scores. The first part revolves around the mentor of Rousseau; a figure of openness. The second part centres on a group of schemers, depicting a period of deep paranoia. We also highlight characters with intermediary roles: they provide narrative links between the societies in the life of the author. The method we detail in this complete case study of character network analysis can be applied to any work documented by an index. Un réseau de personnages modélise les relations entre les personnages d'un récit : les relations sont basées sur une forme de proximité dans le texte, l'apparition commune dans des événements, des citations dans des dialogues, etc. Notre travail propose un cadre théorique pour l'analyse des réseaux de personnages, rassemblant narratologie, close et distant reading, et analyse des réseaux sociaux. Ce travail prolonge les tentatives récentes d'automatisation de l'extraction de réseaux sociaux tirés de la littérature (Elson, 2012; Sack, 2013), ainsi que les études portant sur l'importance des systèmes de personnages (Woloch, 2003; Moretti, 2011). La méthode que nous utilisons pour construire le réseau est directe et simple. Nous extrayons les co-occurrences d'un index sans avoir recours à l'analyse textuelle. Nous décrivons les rôles narratifs des personnages en les déduisant de leurs positions relatives dans le réseau, donc du discours. Comme étude de cas, nous avons choisi le roman autobiographique Les Confessions, de Jean- Jacques Rousseau. Nous déduisons les co-occurrences entre personnages de l'index présent dans l'édition Slatkine (Rousseau et al., 2012). Sur le réseau obtenu, nous calculons quatre types de centralité : le degré, la proximité, l'intermédiarité et la centralité par vecteur propre. Nous utilisons ces mesures pour proposer une typologie des rôles narratifs des personnages. Nous montrons que les deux parties des Confessions, écrites à deux époques différentes, sont structurées autour de deux figures centrales, qui obtiennent des mesures de centralité similaires. La première partie est construite autour du mentor de Rousseau, qui a symbolisé une grande ouverture. La seconde partie se focalise sur un groupe de comploteurs, et retrace une période marquée par la paranoïa chez l'auteur. Nous mettons également en évidence des personnages jouant des rôles intermédiaires, et de fait procurant un lien narratif entre les différentes sociétés couvrant la vie de l'auteur. La méthode d'analyse des réseaux de personnages que nous décrivons peut être appliquée à tout texte de fiction comportant un index.
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We present STAR results on the elliptic flow upsilon(2) Of charged hadrons, strange and multistrange particles from,root s(NN) = 200 GeV Au+Au collisions at the BNL Relativistic Heavy Ion Collider (RHIC). The detailed study of the centrality dependence of upsilon(2) over a broad transverse momentum range is presented. Comparisons of different analysis methods are made in order to estimate systematic uncertainties. To discuss the nonflow effect, we have performed the first analysis Of upsilon(2) with the Lee-Yang zero method for K(S)(0) and A. In the relatively low PT region, P(T) <= 2 GeV/c, a scaling with m(T) - m is observed for identified hadrons in each centrality bin studied. However, we do not observe nu 2(p(T))) scaled by the participant eccentricity to be independent of centrality. At higher PT, 2 1 <= PT <= 6 GeV/c, V2 scales with quark number for all hadrons studied. For the multistrange hadron Omega, which does not suffer appreciable hadronic interactions, the values of upsilon(2) are consistent with both m(T) - m scaling at low p(T) and number-of-quark scaling at intermediate p(T). As a function ofcollision centrality, an increase of p(T)-integrated upsilon(2) scaled by the participant eccentricity has been observed, indicating a stronger collective flow in more central Au+Au collisions.
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Azimuthal angle (Delta phi) correlations are presented for charged hadrons from dijets for 0.4 < p(T)< 10 GeV/c in Au+Au collisions at root s(NN)=200 GeV. With increasing p(T), the away-side distribution evolves from a broad and relatively flat shape to a concave shape, then to a convex shape. Comparisons to p+p data suggest that the away-side can be divided into a partially suppressed ""head"" region centered at Delta phi similar to pi and an enhanced ""shoulder"" region centered at Delta phi similar to pi +/- 1.1. The p(T) spectrum for the head region softens toward central collisions, consistent with the onset of jet quenching. The spectral slope for the shoulder region is independent of centrality and trigger p(T), which offers constraints on energy transport mechanisms and suggests that it contains the medium response to energetic jets.
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We present transverse momentum (p(T)) spectra of charged hadrons measured in deuteron-gold and nucleon-gold collisions at root s(NN)=200 GeV for four centrality classes. Nucleon-gold collisions were selected by tagging events in which a spectator nucleon was observed in one of two forward rapidity detectors. The spectra and yields were investigated as a function of the number of binary nucleon-nucleon collisions, nu, suffered by deuteron nucleons. A comparison of charged particle yields to those in p+p collisions show that yield per nucleon-nucleon collision saturates with nu for high momentum particles. We also present the charged hadron to neutral pion ratios as a function of p(T).
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Forward-backward multiplicity correlation strengths have been measured with the STAR detector for Au + Au and p + p collisions at root s(NN) = 200 GeV. Strong short- and long-range correlations (LRC) are seen in central Au + Au collisions. The magnitude of these correlations decrease with decreasing centrality until only short-range correlations are observed in peripheral Au + Au collisions. Both the dual parton model (DPM) and the color glass condensate (CGC) predict the existence of the long-range correlations. In the DPM, the fluctuation in the number of elementary (parton) inelastic collisions produces the LRC. In the CGC, longitudinal color flux tubes generate the LRC. The data are in qualitative agreement with the predictions of the DPM and indicate the presence of multiple parton interactions.
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Measurements of the centrality and rapidity dependence of inclusive jet production in sNN−−−√=5.02 TeV proton--lead (p+Pb) collisions and the jet cross-section in s√=2.76 TeV proton--proton collisions are presented. These quantities are measured in datasets corresponding to an integrated luminosity of 27.8 nb−1 and 4.0 pb−1, respectively, recorded with the ATLAS detector at the Large Hadron Collider in 2013. The p+Pb collision centrality was characterised using the total transverse energy measured in the pseudorapidity interval −4.9<η<−3.2 in the direction of the lead beam. Results are presented for the double-differential per-collision yields as a function of jet rapidity and transverse momentum (pT) for minimum-bias and centrality-selected p+Pb collisions, and are compared to the jet rate from the geometric expectation. The total jet yield in minimum-bias events is slightly enhanced above the expectation in a pT-dependent manner but is consistent with the expectation within uncertainties. The ratios of jet spectra from different centrality selections show a strong modification of jet production at all pT at forward rapidities and for large pT at mid-rapidity, which manifests as a suppression of the jet yield in central events and an enhancement in peripheral events. These effects imply that the factorisation between hard and soft processes is violated at an unexpected level in proton--nucleus collisions. Furthermore, the modifications at forward rapidities are found to be a function of the total jet energy only, implying that the violations may have a simple dependence on the hard parton--parton kinematics.
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In this paper we study the reconstruction of a network topology from the values of its betweenness centrality, a measure of the influence of each of its nodes in the dissemination of information over the network. We consider a simple metaheuristic, simulated annealing, as the combinatorial optimization method to generate the network from the values of the betweenness centrality. We compare the performance of this technique when reconstructing different categories of networks –random, regular, small-world, scale-free and clustered–. We show that the method allows an exact reconstruction of small networks and leads to good topological approximations in the case of networks with larger orders. The method can be used to generate a quasi-optimal topology fora communication network from a list with the values of the maximum allowable traffic for each node.
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We apply social networks analysis to the study of an important database on investment and companies" share in the Catalonia (Spain) of the nineteenth century. In contrast with most of the existing related literature, usually addressing power relationships across administration boards, we focus on the structure of interactions among individual investors and firms. Centrality analysis uncovers interesting roles played by certain economic sectors (e.g. textile and financial). Furthermore, the diverse composition (in terms of economic activity) of communities in the network (subgroups more densely connected internally than with the rest of the network) reveals a high investment diversification, which nicely agrees with a known characteristic of traditional Catalan business strategies.