scholarly journals Unraveling the Network of the Extractive Industries

2021 ◽  
Author(s):  
Lenin H. Balza ◽  
Camilo De Los Rios ◽  
Alfredo Guerra ◽  
Luis Herrera-Prada ◽  
Osmel Manzano
Keyword(s):  
Network Analysis ◽  
Social Security ◽  
Extractive Industries ◽  
Centrality Measures ◽  
Economic Activities ◽  
Female Workers ◽  
Extractive Sector ◽  
Industrial Network ◽  
Vast Network ◽  
Industry Relatedness

This paper analyzes extractive industries in Colombia and their connections to other economic activities in the country. We use detailed social security data on all formal employees to create an industry-relatedness measure using labor flows between industries. Drawing on the vast network analysis literature, we exploit centrality measures to reveal the importance of the extractive sector among Colombian industries. Our results show that extractive industries are well connected within the Colombian industrial network, and that they are central overall and within their clusters. We also find that extractive industries have stronger linkages with manufacturing and agriculture than with other sectors. Finally, a higher relatedness to extractive activities is correlated with lower levels of employment, specially of female workers.

scholarly journals Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality

Psychometrika ◽  
2021 ◽  
Author(s):  
Oisín Ryan ◽  
Ellen L. Hamaker
Keyword(s):  
Network Analysis ◽  
Discrete Time ◽  
Continuous Time ◽  
Centrality Measures ◽  
Time Interval ◽  
Direct Effects ◽  
Network Approach ◽  
Var Models ◽  
Auto Regressive ◽  
Conceptual Shift

AbstractNetwork analysis of ESM data has become popular in clinical psychology. In this approach, discrete-time (DT) vector auto-regressive (VAR) models define the network structure with centrality measures used to identify intervention targets. However, VAR models suffer from time-interval dependency. Continuous-time (CT) models have been suggested as an alternative but require a conceptual shift, implying that DT-VAR parameters reflect total rather than direct effects. In this paper, we propose and illustrate a CT network approach using CT-VAR models. We define a new network representation and develop centrality measures which inform intervention targeting. This methodology is illustrated with an ESM dataset.

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract Background Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

scholarly journals A New Methodology to Study Street Accessibility: A Case Study of Avila (Spain)

2021 ◽  
Vol 10 (7) ◽  
pp. 491
Author(s):  
Manuel Curado ◽  
Rocio Rodriguez ◽  
Manuel Jimenez ◽  
Leandro Tortosa ◽  
Jose F. Vicent
Keyword(s):  
Network Analysis ◽  
The Other ◽  
Centrality Measures ◽  
Innovative Behavior ◽  
Street Network ◽  
Commercial Activity ◽  
Determining Factors ◽  
Combine Network ◽  
The City

Taking into account that accessibility is one of the most strategic and determining factors in economic models and that accessibility and tourism affect each other, we can say that the study and improvement of one of them involved the development of the other. Using network analysis, this study presents an algorithm for labeling the difficulty of the streets of a city using different accessibility parameters. We combine network structure and accessibility factors to explore the association between innovative behavior within the street network, and the relationships with the commercial activity in a city. Finally, we present a case study of the city of Avila, locating the most inaccessible areas of the city using centrality measures and analyzing the effects, in terms of accessibility, on the commerce and services of the city.

scholarly journals A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Methodological Approach ◽  
Centrality Measures ◽  
Structural Behaviour ◽  
Cross Sectional ◽  
Depth Analysis ◽  
The University

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

Social network analysis applications in sustainable construction and built environment management: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Built Environment ◽  
Methodological Approach ◽  
Relevant Literature ◽  
Sustainable Construction ◽  
Centrality Measures ◽  
Environment Management ◽  
Content Type

PurposeApplications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.Design/methodology/approach95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.FindingsA significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.Originality/valueCloser collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.

scholarly journals Industrial Development and Combating Unemployment in Arab Countries

2019 ◽  
Vol 12 (9) ◽  
pp. 43
Author(s):  
Hussein TRABULSI
Keyword(s):  
Social Security ◽  
Industrial Development ◽  
Statistical Approach ◽  
Arab World ◽  
Arab Countries ◽  
Manufacturing Industries ◽  
Extractive Industries ◽  
Industrial Countries ◽  
Job Opportunities ◽  
Human Density

This research aims to find economic and social solutions through the development of industry in the Arab countries after suffering, for decades, from the lack of interest in order to achieve industrial development and social security, where most of the Arab experiences failed or did not succeed compared to many experiences in the emerging industrial countries. This research addresses the reasons for this failure to achieve industrial development and its effects on economic and social development and contribute to solve the problem of unemployment in most Arab countries. It also contributes to find solutions for industrial development and social security through some proposals. The results of this study also confirmed the existence of policies focusing on the extractive industries, while the manufacturing industries should be interested in achieving industrial development, reducing the unemployment rate and advancing industrial development. The statistical approach and the descriptive and analytical approach were adopted to approach and address the problem of unemployment in the Arab world, which is one of the highest in the world. In the research summary, the importance of investment in the field of manufacturing industries, which depends on the human density, so that the greatest possible number of job opportunities can be created, thus contributing to addressing this problem which threatens the security and stability of most Arab countries. Investment in the food industry, furniture industry and other light manufacturing industries can be a solution to the phenomenon of unemployment in the Arab world, in contrast to industries with a capital density associated with extractive industries.

scholarly journals A Matrix-Variate t Model for Networks

2021 ◽  
Vol 4 ◽  
Author(s):  
Monica Billio ◽  
Roberto Casarin ◽  
Michele Costola ◽  
Matteo Iacopini
Keyword(s):  
Network Analysis ◽  
Measurement Errors ◽  
Statistical Treatment ◽  
Centrality Measures ◽  
Random Errors ◽  
Inference Procedure ◽  
Financial Firms ◽  
The Matrix ◽  
Different Sources ◽  
Flexible Model

Networks represent a useful tool to describe relationships among financial firms and network analysis has been extensively used in recent years to study financial connectedness. An aspect, which is often neglected, is that network observations come with errors from different sources, such as estimation and measurement errors, thus a proper statistical treatment of the data is needed before network analysis can be performed. We show that node centrality measures can be heavily affected by random errors and propose a flexible model based on the matrix-variate t distribution and a Bayesian inference procedure to de-noise the data. We provide an application to a network among European financial institutions.

SAGA OF MIGRANT WORKERS IN INDIA: MEASURES TO STRENGTHEN SOCIAL SECURITY

2020 ◽  
pp. 183-195
Author(s):  
Deepa Pillai ◽  
Leena Dam
Keyword(s):  
Social Security ◽  
Internal Migration ◽  
Migrant Workers ◽  
Large Scale ◽  
State Level ◽  
Policy Formulation ◽  
Economic Activities ◽  
Government Interventions ◽  
Internal Migrants ◽  
Security Standards

COVID 19 pandemic has thrown up bitter colors when India witnessed the large scale gory sage of reverse internal migration of unorganized workforce. As compared to intercontinental migration the degree of internal migration is twice. Displacement, lockdowns, loss of employment, starvation and social distancing provoked a frenzied course of mass return for internal migrants in India and other parts of the world. In India there is a peculiar trend of unorganized workforce migration. Out of 29 states and 7 union territories, few states dominate where migrants flock for seeking livelihood. The fleeing of migrants to their inherent origin has weakened the economic activities towards slowdown in the economic growth. This thematic review paper discusses the problems of the internal migrants and their state during and post lockdown announcements in India. The data included extracts of articles, opinions and reviews for which codes were recognized which lead to formulation of research themes. The review also highlights government interventions in addressing the challenges confronted by the internal migrants with social security. This study proposes an arrangement as migrant exchange at state level for efficient policy formulation and accomplishment of social security standards.

Exploring Network Analysis for Urban Planning and Disaster Risk Reduction in Informal Settlements

2020 ◽  
Vol 3 (1) ◽  
pp. 30-45
Author(s):  
Vicente Sandoval ◽  
Juan Pablo Sarmiento ◽  
Erick Alberto Mazariegos ◽  
Daniel Oviedo
Keyword(s):  
Network Analysis ◽  
Urban Planning ◽  
Risk Reduction ◽  
Disaster Risk Reduction ◽  
Informal Settlements ◽  
Disaster Risk ◽  
Centrality Measures ◽  
Analysis Tool ◽  
Urban Resilience ◽  
Street Networks

The work explores the use of street network analysis on informal settlements and discusses the potential and limitations of this methodology to advance disaster risk reduction and urban resilience. The urban network analysis tool is used to conduct graph analysis measures on street networks in three informal settlements in the LAC region: Portmore, Jamaica; Tegucigalpa, Honduras; and Lima, Peru. Authors incorporate risk variables identified by these communities and combine them with prospective scenarios in which street networks are strategically intervened to improve performance. Authors also compute one graph index named Reach centrality. Results are presented spatially through thematic maps, and statistically by plotting cumulative distributions. Findings show that centrality measures of settlements' networks helped identify key nodes or roads that may be critical for people's daily life after disasters, and strategic to improve accessibility. The proposed methodology shows potential to inform decisions on urban planning and disaster risk reduction.

scholarly journals Expanding Network Analysis Tools in Psychological Networks: Minimal Spanning Trees, Participation Coefficients, and Motif Analysis Applied to a Network of 26 Psychological Attributes

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-27 ◽  
Author(s):  
Srebrenka Letina ◽  
Tessa F. Blanken ◽  
Marie K. Deserno ◽  
Denny Borsboom
Keyword(s):  
Network Analysis ◽  
Spanning Trees ◽  
Main Idea ◽  
Global Network ◽  
Centrality Measures ◽  
Future Research ◽  
Motif Analysis ◽  
Psychological Variables ◽  
Hierarchical Arrangement ◽  
Psychological Attributes

The analysis of psychological networks in previous research has been limited to the inspection of centrality measures and the quantification of specific global network features. The main idea of this paper is that a psychological network entails more potentially useful and interesting information that can be reaped by other methods widely used in network science. Specifically, we suggest methods that provide clearer picture about hierarchical arrangement of nodes in the network, address heterogeneity of nodes in the network, and look more closely at network’s local structure. We explore the potential value of minimum spanning trees, participation coefficients, and motif analyses and demonstrate the relevant analyses using a network of 26 psychological attributes. Using these techniques, we investigate how the network of different psychological concepts is organized, which attribute is most central, and what the role of intelligence in the network is relative to other psychological variables. Applying the three methods, we arrive at several tentative conclusions. Trait Empathy is the most “central” attribute in the network. Intelligence, although peripheral, is weakly but equally related to different kinds of attributes present in the network. Analysis of triadic configurations additionally shows that the network is characterized by relatively strong open triads and an unusually frequent occurrence of negative triangles. We discuss these and other findings in the light of possible theoretical explanations, methodological limitations, and future research.

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