Foreign Capital and Economic Growth: A Social Network Analysis, 2001–2017

2021 ◽  
pp. 073112142110351
Author(s):  
Rob Clark ◽  
Jeffrey Kentor
Keyword(s):  
Economic Growth ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Direct Investment ◽  
Fixed Effects ◽  
Foreign Capital ◽  
Global Network ◽  
Data Sets ◽  
The Impact

Foreign direct investment (FDI) holds a substantial and rapidly growing presence across every region of the world. However, our understanding of how foreign capital impacts economic growth in receiving and investing countries remains in question, despite nearly five decades of research. Our study contributes to this long-standing debate by (1) applying social network analysis to the FDI-growth literature, (2) utilizing recently available bilateral data for a global sample of countries during the post-2000 period, and (3) examining the impact of both inward and outward foreign capital on economic growth. While conventional measures of FDI typically focus on investment volume, we argue that the network structure of investment relations may be equally—or more—important. We construct a global network of FDI during the 2001–2017 period, bringing together two data sets: (1) the United Nations Conference on Trade and Development’s Bilateral FDI Statistics, and (2) the International Monetary Fund’s Coordinated Direct Investment Survey. We then calculate network centrality scores that reflect each country’s level of inward and outward embeddedness in the global FDI network. Drawing from a sample of 1,467 observations across 137 countries during the 2001–2017 period, we estimate two-way fixed effects models to examine the effect of FDI centrality on economic growth. Net of other predictors, we find that inward and outward centrality are positively—and independently—associated with growth, while more conventional measures of foreign capital display weaker and inconsistent effects.

Measuring the Impact of Social Media

2011 ◽  
pp. 24-36 ◽  
Author(s):  
Kimiz Dalkir
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Evaluation Method ◽  
Real Life ◽  
Work Processes ◽  
The Social ◽  
Post Test ◽  
The Impact

This chapter focuses on a method, social network analysis (SNA) that can be used to assess the quantity and quality of connection, communication and collaboration mediated by social tools in an organization. An organization, in the Canadian public sector, is used as a real-life case study to illustrate how SNA can be used in a pre-test/post-test evaluation design to conduct a comparative assessment of methods that can be used before, during and after the implementation of organizational change in work processes. The same evaluation method can be used to assess the impact of introducing new social media such as wikis, expertise locator systems, blogs, Twitter and so on. In other words, while traditional pre-test/post-test designs can be easily applied to social media, the social media tools themselves can be added to the assessment toolkit. Social network analysis in particular is a good candidate to analyze the connections between people and content as well as people with other people.

Introduction

2020 ◽  
pp. 1-29
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Structure ◽  
Research Methods ◽  
The Other ◽  
Traditional Research ◽  
The Social ◽  
Social Realm ◽  
The Impact

The traditional research approaches common in different disciplines of social sciences centered around one half of the social realm: the actors. The other half are the relations established by these actors and forming the basis of “social.” The social structure shaped by these relations, the position of the actor within this structure, and the impact of this position on the actor are mostly excluded by the traditional research methods. In this chapter, the authors introduce social network analysis and how it complements the other methods.

Social Network Analysis in Child and Adolescent Physical Activity Research: A Systematic Literature Review

2020 ◽  
Vol 17 (2) ◽  
pp. 250-260 ◽  
Author(s):  
Tyler Prochnow ◽  
Haley Delgado ◽  
Megan S. Patterson ◽  
M. Renée Umstattd Meyer
Keyword(s):  
Physical Activity ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Children And Adolescents ◽  
Child And Adolescent ◽  
Adolescent Physical Activity ◽  
Final Sample ◽  
Network Composition ◽  
The Impact

Background: Regular physical activity (PA) has many benefits for children and adolescents, yet many do not meet PA recommendations. Social context is important for promoting or discouraging PA among children and adolescents. This review aimed to identify social network variables related to PA among children and adolescents. Methods: A systematic review of the literature was conducted in September 2018 using PsycINFO, MEDLINE, PubMed, and Web of Science. Included articles needed to (1) be focused on children (aged 5–11 y) or adolescents (aged 12–17 y), (2) include a measure of PA, (3) include a measure of egocentric or sociocentric social connection in which alters were nominated, and (4) perform an analysis between network data and PA. Results: A search of 11,824 articles was refined to a final sample of 29 articles. Social network themes and concepts such as homophily, centrality, and network composition were related to child and adolescent PA behavior across the literature. Conclusions: The impact of an individual’s social network is evident on their PA behaviors. More research is needed to examine why these networks form in relation to PA and how interventions can utilize social network analysis to more effectively promote PA, especially in underserved and minority populations.

Network Redundancy and Information Diffusion: The Impacts of Information Redundancy, Similarity, and Tie Strength

2016 ◽  
Vol 46 (2) ◽  
pp. 250-272 ◽  
Author(s):  
Hai Liang ◽  
King-wa Fu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Diffusion ◽  
Tie Strength ◽  
Information Redundancy ◽  
Ego Networks ◽  
Core Concepts ◽  
The Impact

It remains controversial whether community structures in social networks are beneficial or not for information diffusion. This study examined the relationships among four core concepts in social network analysis—network redundancy, information redundancy, ego-alter similarity, and tie strength—and their impacts on information diffusion. By using more than 6,500 representative ego networks containing nearly 1 million following relationships from Twitter, the current study found that (1) network redundancy is positively associated with the probability of being retweeted even when competing variables are controlled for; (2) network redundancy is positively associated with information redundancy, which in turn decreases the probability of being retweeted; and (3) the inclusion of both ego-alter similarity and tie strength can attenuate the impact of network redundancy on the probability of being retweeted.

scholarly journals Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration

2014 ◽  
Vol 8 (2) ◽  
pp. 150-154 ◽  
Author(s):  
Radhakrishnan Nagarajan ◽  
Charlotte A. Peterson ◽  
Jane S. Lowe ◽  
Stephen W. Wyatt ◽  
Timothy S. Tracy ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biomedical Research ◽  
The Impact ◽  
Research Grant

scholarly journals Assessing the impact of socio-technical congruence in software development: a systematic literature review

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Binish Raza ◽  
◽  
Rodina Ahmad ◽  
Mohd H.N.M Nasir ◽  
Shukor S.M Fauzi ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Literature Review ◽  
Software Development ◽  
Systematic Literature Review ◽  
Measurement Techniques ◽  
Evolutionary Trends ◽  
Team Members ◽  
The Impact

Software development is a critical task that depends on coordination among team members and organizational activities that bring team members together. The literature indicates various techniques that have been applied to control the coordination level among team members. Notable among these techniques is social-technical congruence (STC), which helps to measure the alignment between the social and technical capabilities of an organization and teams at various stages of software development. The dynamic nature and changes of coordination requirements make STC a potential research area in this regard. The main objective of this study is to perform a systematic literature review (SLR) that recognizes and structures existing studies that represent new evolutionary trends in the field of STC. A SLR is performed of 46 publications from 4 data sources, including journals, conferences and workshop proceedings, most of which were published between 2008 and 2019. To this end, a thorough analysis is carried out to elicit the studies based on 7 research questions in this SLR. The outcome of this SLR is a set of ample research studies representing various aspects, performance impacts, factors, and evolutionary trends in the field of STC. Furthermore, STC measurement techniques are classified in two distinct groups, matrix based and social network analysis-based measures. After a systematic exploration of these aspects, this study results in new insightful features and state of art of STC. This SLR concludes that some areas still require further investigation. For instance, (1) STC-related literature exists, but only one research work mainly focuses on the risk of overwhelming STC (i.e., excessive STC measurement may overburden the software development process); (2) STC measurement techniques facilitate the identification of congruence gaps, but no attention has been given towards the unweighted social network analysis based STC measurement models; (3) STC measurement techniques are generally applied in the development phase of the project lifecycle, but these measurements are rarely used in other software development phases, such as the requirement and testing phases or all phases; and (4) The development factors that effects on STC measurement are rarely focused by researchers in the context of various domains.

scholarly journals Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pilar Marqués-Sánchez ◽  
Arrate Pinto-Carral ◽  
Tania Fernández-Villa ◽  
Ana Vázquez-Casares ◽  
Cristina Liébana-Presa ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Global Network ◽  
Case Study Methodology ◽  
And Gender ◽  
The One ◽  
Relationship Structure ◽  
The University

AbstractThe aims: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan–Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan–Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

Family Relationships and Adolescent Loneliness: An Application of Social Network Analysis in Family Studies

2020 ◽  
Author(s):  
Saeideh Heshmati ◽  
Megan Blackard ◽  
Blake Beckmann ◽  
Wallace Chipidza
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Family Relationships ◽  
Family Income ◽  
Family Systems Theory ◽  
High Quality ◽  
The Family ◽  
The Impact ◽  
Quality Relationships

In family contexts, individuals are embedded in networks of relationships. Social Network Analysis (SNA) provides a unique framework to investigate family relationships as interrelated networks above and beyond dyadic familial relationships. In the current paper, we used the notion of triadic closure to investigate how various configurations of family networks, classified by their relationship ties, differ in predicting adolescents’ experiences of loneliness. We classified different types of network structures based on whether all three family members (i.e., child, mother, father) shared high quality relationships with one another (closed) or whether one or more low quality ties existed in the family triad (open). Results indicated that, compared to adolescents in families containing one or more poor-quality ties, adolescents in families containing all high-quality relational ties experienced lower levels of loneliness, above and beyond the impact of gender, parents’ education and mental health, and family income. Simply put, adolescents’ experiences of loneliness is not tied to the number of high quality relationships they experience within the family, rather is dependent on the presence of high quality relationships among all family ties. With the introduction of one low-quality relationship within a family triad, additional low-quality relationships appear to make little difference. In line with family systems theory, our examination of the family as a whole, rather than as a summative combination of smaller relationships, indicates that a closed family structure is important for protecting adolescents against experiences of loneliness.

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