Reconstruction of networks from their betweenness centrality

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.

Centrality dependence of charged hadron and strange hadron elliptic flow from root s(NN)=200 GeVAu+Au collisions

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.

Transverse momentum and centrality dependence of dihadron correlations in Au plus Au collisions at root s(NN)=200 GeV: Jet quenching and the response of partonic matter

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.

Centrality dependence of charged hadron production in deuteron plus gold and nucleon plus gold collisions at root S(NN)=200 GeV

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).

Growth of Long Range Forward-Backward Multiplicity Correlations with Centrality in Au plus Au Collisions at root s(NN)=200 GeV

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.

Centrality and rapidity dependence of inclusive jet production in sNN=5.02 TeV proton-lead collisions with the ATLAS detector

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.

Character Networks and Centrality

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.

Centrality and investment strategies at the beginning of industrialisation in mid-nineteenth-century Catalonia

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.

Betweenness Centrality in Some Classes of Graphs

There are several centrality measures that have been introduced and studied for real world networks. They account for the different vertex characteristics that permit them to be ranked in order of importance in the network. Betweenness centrality is a measure of the influence of a vertex over the flow of information between every pair of vertices under the assumption that information primarily flows over the shortest path between them. In this paper we present betweenness centrality of some important classes of graphs.

Centrality and spectral radius in dynamic communication networks

We explore the influence of the choice of attenuation factor on Katz centrality indices for evolving communication networks. For given snapshots of a network observed over a period of time, recently developed communicability indices aim to identify best broadcasters and listeners in the network. In this article, we looked into the sensitivity of communicability indices on the attenuation factor constraint, in relation to spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We proposed relaxed communicability measures where the spectral radius bound on attenuation factor is relaxed and the adjacency matrix is normalised in order to maintain the convergence of the measure. Using a vitality based measure of both standard and relaxed communicability indices we looked at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We illustrated our findings with two examples of real-life networks, MIT reality mining data set of daily communications between 106 individuals during one year and UK Twitter mentions network, direct messages on Twitter between 12.4k individuals during one week.

On the radius of centrality in evolving communication networks

In this article, we investigate how the choice of the attenuation factor in an extended version of Katz centrality influences the centrality of the nodes in evolving communication networks. For given snapshots of a network, observed over a period of time, recently developed communicability indices aim to identify the best broadcasters and listeners (receivers) in the network. Here we explore the attenuation factor constraint, in relation to the spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We compare three different communicability measures: standard, exponential, and relaxed (where the spectral radius bound on the attenuation factor is relaxed and the adjacency matrix is normalised, in order to maintain the convergence of the measure). Furthermore, using a vitality-based measure of both standard and relaxed communicability indices, we look at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We compare those measures with the scores produced by an iterative version of the PageRank algorithm and illustrate our findings with two examples of real-life evolving networks: the MIT reality mining data set, consisting of daily communications between 106 individuals over the period of one year, a UK Twitter mentions network, constructed from the direct \emph{tweets} between 12.4k individuals during one week, and a subset the Enron email data set.