scholarly journals Interlocking directorates and different power forms: An explorative analysis in the Italian context

2018 ◽  
Vol 14 (2) ◽  
pp. 7-19 ◽  
Author(s):  
Salvatore Esposito De Falco ◽  
Nicola Cucari ◽  
Federica Di Franco
Keyword(s):  
Betweenness Centrality ◽  
Power Structure ◽  
Centrality Measures ◽  
Network Density ◽  
Weighted Sum ◽  
Eigenvector Centrality ◽  
Interlocking Directorates ◽  
The Social ◽  
Italian Context ◽  
Cross Shareholdings

The purpose of the present paper is twofold. The first is to update the contribution by Drago et al. (2011) about cross-shareholdings and interlocking directorates in Italian listed companies (FTSE MIB) to 31 December 2016 and to reinforce theory of enlarged collusion. The second is to find how interlocking directorates can contribute to understanding the power structure. By using the social network analysis, we map the network structure of interlocking boards and employ centrality measures like degree, eigenvector and betweenness centrality along with the network density and average degree. We interpret eigenvector centrality as a measure of “effective power” of the connections because it can be seen as a weighted sum of not only direct connections but indirect connections, while betweenness centrality as a measure of “potential power” because it is a proxy of the volume of information that passes through the nodes. In this way, we provide a framework for selecting Italian firms with effective and potential power – around whom interactions and processes can be traced and analysed. In addition, we find that the position assumed by the controlling group of the Mediobanca Galaxy is definitely downsized.

Use of Centrality Metrics for Ranking of Courses Based on Their Relative Contribution in a Curriculum Network Graph

2018 ◽  
pp. 129-159
Keyword(s):  
Betweenness Centrality ◽  
Directed Acyclic Graph ◽  
Degree Centrality ◽  
Weighted Sum ◽  
Eigenvector Centrality ◽  
Network Graph ◽  
Curriculum Assessment ◽  
Acyclic Graph ◽  
Relative Contribution ◽  
Centrality Metrics

The author proposes a centrality and topological sort-based formulation to quantify the relative contribution of courses in a curriculum network graph (CNG), a directed acyclic graph, comprising of the courses (as vertices), and their pre-requisites (captured as directed edges). The centrality metrics considered are out-degree and in-degree centrality along with betweenness centrality and eigenvector centrality. The author normalizes the values obtained for each centrality metric as well as the level numbers of the vertices in a topological sort of the CNG. The contribution score for a vertex is the weighted sum of the normalized values for the vertex. The author observes the betweenness centrality of the vertices (courses) to have the largest influence in the relative contribution scores of the courses that could be used as a measure of the weights to be given to the courses for curriculum assessment and student ranking as well as to cluster courses with similar contribution.

Centrality Measures

2018 ◽  
Author(s):  
Ginestra Bianconi
Keyword(s):  
State Of The Art ◽  
Centrality Measures ◽  
Eigenvector Centrality ◽  
Multilayer Networks ◽  
Comprehensive Description ◽  
Multilayer Network ◽  
Suitable Definition ◽  
Katz Centrality ◽  
Pagerank Centrality

Defining the centrality of nodes and layers in multilayer networks is of fundamental importance for a variety of applications from sociology to biology and finance. This chapter presents the state-of-the-art centrality measures able to characterize the centrality of nodes, the influences of layers or the centrality of replica nodes in multilayer and multiplex networks. These centrality measures include modifications of the eigenvector centrality, Katz centrality, PageRank centrality and Communicability to the multilayer network scenario. The chapter provides a comprehensive description of the research of the field and discusses the main advantages and limitations of the different definitions, allowing the readers that wish to apply these techniques to choose the most suitable definition for his or her case study.

scholarly journals Centrality-friendship paradoxes: when our friends are more important than us

2018 ◽  
Vol 7 (4) ◽  
pp. 515-528 ◽  
Author(s):  
Desmond J Higham
Keyword(s):  
Network Science ◽  
Sufficient Conditions ◽  
Sampling Bias ◽  
Average Degree ◽  
Science Literature ◽  
Eigenvector Centrality ◽  
General Matrix ◽  
Theoretical Support ◽  
The Social ◽  
Katz Centrality

Abstract The friendship paradox states that, on average, our friends have more friends than we do. In network terms, the average degree over the nodes can never exceed the average degree over the neighbours of nodes. This effect, which is a classic example of sampling bias, has attracted much attention in the social science and network science literature, with variations and extensions of the paradox being defined, tested and interpreted. Here, we show that a version of the paradox holds rigorously for eigenvector centrality: on average, our friends are more important than us. We then consider general matrix-function centrality, including Katz centrality, and give sufficient conditions for the paradox to hold. We also discuss which results can be generalized to the cases of directed and weighted edges. In this way, we add theoretical support for a field that has largely been evolving through empirical testing.

Comparison and Application of Metrics That Define the Components Modularity in Complex Products

2008 ◽  
Author(s):  
Qi D. Van Eikema Hommes
Keyword(s):  
Social Network ◽  
Centrality Measures ◽  
Software Systems ◽  
Network Centrality ◽  
Good Pair ◽  
Centrality Metrics ◽  
The Social ◽  
Social Network Centrality ◽  
Sample Test

As the content and variety of technology increases in automobiles, the complexity of the system increases as well. Decomposing systems into modules is one of the ways to manage and reduce system complexity. This paper surveys and compares a number of state-of-art components modularity metrics, using 8 sample test systems. The metrics include Whitney Index (WI), Change Cost (CC), Singular value Modularity Index (SMI), Visibility-Dependency (VD) plot, and social network centrality measures (degree, distance, bridging). The investigation reveals that WI and CC form a good pair of metrics that can be used to assess component modularity of a system. The social network centrality metrics are useful in identifying areas of architecture improvements for a system. These metrics were further applied to two actual vehicle embedded software systems. The first system is going through an architecture transformation. The metrics from the old system revealed the need for the improvements. The second system was recently architected, and the metrics values showed the quality of the architecture as well as areas for further improvements.

Le seconde generazioni: nodi critici e nuove forme di integrazione

2009 ◽  
pp. 25-46
Author(s):  
Elena Caneva ◽  
Maurizio Ambrosini
Keyword(s):  
Immigrant Families ◽  
Cultural Transformation ◽  
Religious Organizations ◽  
Ethnic Communities ◽  
Ethnic Networks ◽  
The Social ◽  
Italian Context ◽  
Human And Social Capital ◽  
Analytical Approaches

- The number of immigrant children in Italy has been increasing more and more. They are impacting both on immigration as a phenomenon and on receiving societies. Thus, it becomes important and useful to understand which factors matter in second generation's paths and potential trajectories. Through a presentation of different analytical approaches on the phenomenon of migration, the paper explores the role of the family, the ethnic community and friends, as well as of religion and religious organizations in the promotion or prevention of positive forms of inclusion. With a specific focus on the Italian context, it explains the social and cultural transformation that characterises immigrant families, stressing the role that can be played by the human and social capital embedded in ethnic networks. The main aim of this paper is to go beyond the assimilation approaches and to highlight how immigrant families, ethnic networks and religious organizations could promote integration and the upward mobility of future generations. Keywords: Immigration, Second Generation, Ethnic Communities, Integration, Social Cohesion.

scholarly journals Changing Social Focusing in Indigenous Social Movements

2014 ◽  
Vol 11 (1/2) ◽  
Author(s):  
J. David Flynn ◽  
James M. Hay
Keyword(s):  
Social Sciences ◽  
Social Movements ◽  
Social Movement ◽  
Social System ◽  
Centrality Measures ◽  
Northern Ontario ◽  
The Social ◽  
Incoming Information ◽  
Indigenous Social Movements ◽  
Self Immolation

Using complexity science, we develop a theory to explain why some social movements develop through stages of increasing intensity which we define as an increase in  social focusing. We name six such stages of focusing: disintegration, revitalization, religious, organisation, militaristic, and self-immolation. Our theory uses two variables from the social sciences: differentiation and centrality, where differentiation refers to the internal structure of a social system and centrality measures the variety of incoming information. The ratio of the two, differentiation/centrality (the d/c ratio) is a shorthand way of saying that centrality must be matched by a corresponding level of differentiation to maintain basic focusing. If centrality exceeds differentiation, then the result is a lack of focusing—disintegration. On the other hand, the more differentiation exceeds centrality, the more the system moves into the higher stages of social focusing, from revitalization to the final stage of self-immolation.   To test the theory we examine historically indigenous social movements, in particular, the Grassy Narrows movement in northern Ontario Canada. We also suggest how the theory might be applied to explain other examples of social movement, especially millenarian movements at the end of the 20th century. We also suggest sociocybernetic ways the rest of society and the social movement itself can change its own social focusing.

scholarly journals A COMPARISON OF CENTRALITY MEASURES IN SUSTAINABLE DEVELOPMENT GOALS

2020 ◽  
Vol 14 (3) ◽  
pp. 309-320
Author(s):  
Sena Ariesandy ◽  
Ema Carnia ◽  
Herlina Napitupulu
Keyword(s):  
Sustainable Development ◽  
Millennium Development Goals ◽  
Sustainable Development Goals ◽  
Closeness Centrality ◽  
Centrality Measures ◽  
Degree Centrality ◽  
Eigenvector Centrality ◽  
Global Problems ◽  
Calculation Results ◽  
Development Goals

The Millennium Development Goals (MDGs), which began in 2000 with 8 goal points, have not been able to solve the global problems. The MDGs were developed into Sustainable Development Goals (SDGs) in 2015 with 17 targeted goal points achieved in 2030. Until now, methods for determining the priority of SDGs are still attractive to researchers. Centrality is one of the tools in determining the priority goal points on a network by using graph theory. There are four measurements of centrality used in this paper, namely degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The calculation results obtained from the four measurements are compared, analyzed, to conclud which goal points are the most prior and the least prior. From the results obtained the most priority goal points in Sustainable Development Goals.

Analyzing Work Teams Using Social Network Diagrams

2014 ◽  
pp. 170-191
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Social Network ◽  
Social Dynamics ◽  
Power Structure ◽  
Work Team ◽  
Team Members ◽  
The Social ◽  
Workplace Teams ◽  
Project Phases ◽  
Shed Light ◽  
Network Diagrams

Workplace teams are a common social structure that enables the successful completion of collaborative projects. They have been studied as “hot” teams, virtual ones, and other manifestations. For both management and team members, it is helpful to have a form of meta-cognition on teams to solve work team issues pre-, during-, and post-project. One way to systematize understandings of a work team is to apply social network analysis to depict the work team’s power structure, its functions, and ways to improve the team’s communications for productivity, creativity, and effective functioning. This chapter depicts three real-world team-based projects as social network diagrams along with some light analysis. This work finds that social network diagrams may effectively shed light on the social dynamics of projects in the pre-, during-, and post-project phases.

Computationally Light vs. Computationally Heavy Centrality Metrics

2018 ◽  
pp. 34-65
Keyword(s):  
Betweenness Centrality ◽  
Clustering Coefficient ◽  
Degree Centrality ◽  
Strongly Correlated ◽  
Eigenvector Centrality ◽  
Correlation Measure ◽  
Centrality Metrics ◽  
Two Measures ◽  
Local Clustering Coefficient ◽  
Spearman’S Correlation

In this chapter, the authors analyze the correlation between the computationally light degree centrality (DEG) and local clustering coefficient complement-based degree centrality (LCC'DC) metrics vs. the computationally heavy betweenness centrality (BWC), eigenvector centrality (EVC), and closeness centrality (CLC) metrics. Likewise, they also analyze the correlation between the computationally light complement of neighborhood overlap (NOVER') and the computationally heavy edge betweenness centrality (EBWC) metric. The authors analyze the correlations at three different levels: pair-wise (Kendall's correlation measure), network-wide (Spearman's correlation measure), and linear regression-based prediction (Pearson's correlation measure). With regards to the node centrality metrics, they observe LCC'DC-BWC to be the most strongly correlated at all the three levels of correlation. For the edge centrality metrics, the authors observe EBWC-NOVER' to be strongly correlated with respect to the Spearman's correlation measure, but not with respect to the other two measures.

Change point detection in social networks using a multivariate exponentially weighted moving average chart

2019 ◽  
Vol 46 (6) ◽  
pp. 790-809
Author(s):  
Ali Salmasnia ◽  
Mohammadreza Mohabbati ◽  
Mohammadreza Namdar
Keyword(s):  
Social Networks ◽  
Control Chart ◽  
Change Point ◽  
Moving Average ◽  
Change Point Detection ◽  
Network Density ◽  
Exponentially Weighted Moving Average ◽  
The Social ◽  
Point Detection ◽  
Weighted Moving Average

Although the significant role of social networks in communications between individuals has attracted researchers’ attention to the social networks, only few authors investigated social network monitoring in their studies. Most of the existing studies in this context suffer from the following three main drawbacks: (1) using the case-based network attributes such as person experiences and departments instead of the main attributes such as network density and centrality attributes, (2) monitoring the social attributes separately with the assumption that they are independent of each other and (3) ignoring detection of real time of change in the network. To overcome the above-mentioned disadvantages, this research develops a statistical method for monitoring the connections among actors in the social networks with the four most important network attributes consisting of (1) network density, (2) degree centrality, (3) betweenness centrality and (4) closeness centrality. To this end, a multivariate exponentially weighted moving average (MEWMA) control chart is used for simultaneous monitoring of these four correlated attributes. Furthermore, since the control chart usually does not alert a signal in the exact time of change due to type II error, this study presents a change point detection method to reduce cost and time required for diagnosing the control chart signal. Eventually, the efficiency of the proposed approach in comparison with the existing methods is evaluated through a simulation procedure. The results indicate that the suggested method has better performance than the univariate approach in detecting change point.

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