Search results for "centrality"

An Analysis of the Internal Organization of Facebook Groups

2019

With the rapid development and growth of online social networks (OSNs), researchers have been pushed forward to improve the knowledge of these complex networks by analyzing several aspects, such as the types of social media, the structural properties of the network, or the interaction patterns among users. In particular, a relevant effort has been devoted to the study and identification of cohesive groups of users in OSNs (also referred as communities) because they are the basic building block of each OSN. While several research works on groups in OSNs have mainly focused on identifying the types of groups and the contents created by their members, the analysis of internal organizations of …

Network Centralities and Node Ranking

2017

An important problem in network analysis is understanding how much nodes are important in order to “propagate” the information across the input network. To this aim, many centrality measures have been proposed in the literature and our main goal here is that of providing an overview of the most important of them. In particular, we distinguish centrality measures based on walks computation from those based on shortest-paths computation. We also provide some examples in order to clarify how these measures can be calculated, with special attention to Degree Centrality, Closeness Centrality and Betweennes Centrality.

k-Truss Decomposition for Modular Centrality

2018

There is currently much interest in identifying influential spreaders in complex networks due to many applications concerned, such as controlling the outbreak of epidemics and conducting advertisements for commercial products, and so on. A plethora of centrality measures have been proposed over the years based on the topological properties of networks. However, most of these classical centrality measures fail to select the most influential nodes in networks with a modular structure despite that it is an omnipresent property in real-world networks. Few authors have introduced centrality measures tailored to networks with community structure. In a recent work, we have shown that, in this case…

2020

While most of opinion formation models consider static networks, a dynamic opinion formation model is proposed in this work. The so-called Temporal Threshold Page Rank Opinion Formation model (TTPROF) integrates temporal evolution in two ways. First, the opinion of the agents evolve with time. Second, the network structure is also time varying. More precisely, the relations between agents evolve with time. In the TTPROF model, a node is affected by part of its neighbor's opinions weighted by their Page Rank values. A threshold is introduced in order to limit the neighbors that can share their opinion. In other words, a neighbor influences a node if the difference between their opinions is b…

Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

2021

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…

Game of Thieves and WERW-Kpath: Two Novel Measures of Node and Edge Centrality for Mafia Networks

2021

Real-world complex systems can be modeled as homogeneous or heterogeneous graphs composed by nodes connected by edges. The importance of nodes and edges is formally described by a set of measures called centralities which are typically studied for graphs of small size. The proliferation of digital collection of data has led to huge graphs with billions of nodes and edges. For this reason, we focus on two new algorithms, Game of Thieves and WERW-Kpath which are computationally-light alternatives to the canonical centrality measures such as degree, node and edge betweenness, closeness and clustering. We explore the correlation among these measures using the Spearman’s correlation coefficient …

A Contribution to the Categories of Social Time and the Economy of Time

1977

The article strives to demonstrate the centrality of the category of social time (a) in people's daily lives, (b) as a methodological tool in the study of social process, and (c) as a means towards the planned development and management of advanced societies. Social time has two aspects: rhythm of life and available total time. The article shows that in advanced societies total time and its rational allocation are central in the development of society and individual personality. The nature of social time in less developed societies is also reviewed as well as the historical development of time awareness and the problems of the research on time budget. The article is based on the conception…

The Urban-Rural Continuum. The Bioclimatic Approach to Design, Between Past and Future

2021

L’ambiente costruito rurale, insieme multiscalare di trasformazioni praticate dall’uomo per accogliere le attività collegate all’agricoltura, suggerisce varie riflessioni sull’approccio bioclimatico nel progetto di architettura. Il contributo mette subito in evidenza il tema del continuum urbano-rurale (luogo intermedio e contraddittorio che condensa le trasformazioni che stanno avvenendo nella contemporaneità, offrendo un banco di prova necessario per tutti i campi del sapere e per tutte le discipline tecnologiche) per evidenziare che la contrapposizione tra urbano e rurale non solo è superata nei fatti, ma anche è teoricamente inadeguata a identificare l’ambiente costruito rurale, nonosta…

Publication Network Analysis of an Academic Family in Information Systems

2011

The study of scientific collaboration through network analysis can give interesting conclusions about the publication habits of a scientific community. Co-authorship networks represent scientific collaboration as a graph: nodes correspond to authors, edges between nodes mark joint publications (Newman 2001a,b). Scientific publishing is decentralized. Choices of co-authors and research topics are seldomly globally coordinated. Still, the structure of co-authorship networks is far from random. Co-authorship networks are governed by principles that are similar in other complex networks such as social networks (Wasserman and Faust 1994), networks of citations between scientific papers (Egghe an…

"Table 10" of "Measurement of very forward energy and particle production at midrapidity in pp and p-Pb collisions at the LHC"

2022

p-remnant side ZN signal normalized to MB value vs. average Ncoll in p-Pb collisions at 8.16 TeV