A Study on the Social Recognition of Public Education for Infants in Korea: Focusing on Big Data and Social Network Analysis

2020 ◽  
Vol 11 (2) ◽  
pp. 1487-1502
Author(s):  
Boyeon Kim ◽  
Jiyoung Choi
2021 ◽  
Vol 27 (5) ◽  
pp. 1139-1145
Author(s):  
Ran-Sug Seo

The purpose of this study was to identify the social phenomena of tattoo, which have been of constant interest in our society, through analysis of social networks collected from big data on what the social phenomena implied in keywords emphasized in newspaper articles over the past year. To this end, by analyzing keywords about tattoos that frequently appeared in newspaper articles, we could see what the main interests of social phenomena related to tattoos were. Data on tattoos were collected from newspaper articles over the past year and analyzed how they formed meaning regarding the relationship structure and centrality between the keywords at issue through social network analysis. These findings provide basic data on social discussions and policy directions related to tattoos in practice and discussions related to ways to improve them. This study is an extension from existing quantitative research by analyzing the social phenomena of tattoos through Bigdata and social network analysis. Apart from statistical surveys or subjective qualitative research, we have approached them with content analysis using big data and social network analysis. The conclusion of this study is as follows. First, as a result of analyzing the word cloud regarding tattoos, it was confirmed that “rose” and “300” were the most prominent, and there were keywords that could analyze various other social phenomena. Second, as a result of analysis by connection centrality, it was proved that the social interest and popularity of tattoos increased. Third, as a result of analysis by eigenvector centrality, the popularity of tattoos was proved. It objectified academic research by attempting research from a different perspective from the analysis of research trends and provided visualized research results of readers.


Author(s):  
Sophie Mützel ◽  
Ronald Breiger

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.


Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.


2015 ◽  
Vol 6 (1) ◽  
pp. 30-34 ◽  
Author(s):  
Iraj Mohammadfam ◽  
Susan Bastani ◽  
Mahbobeh Esaghi ◽  
Rostam Golmohamadi ◽  
Ali Saee

2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell

PurposeThe authors evaluate the evolution of the intellectual structure of strategic management (SM) by employing a document co-citation analysis through a network analysis for academic citations in articles published in the Strategic Management Journal (SMJ).Design/methodology/approachThe authors employed the co-citation analysis through the social network analysis.FindingsThe authors outlined the evolution of the academic foundations of the structure and emphasized several domains. The economic foundation of SM research with macro and micro perspectives has generated a solid knowledge stock in the literature. Industrial organization (IO) psychology has also been another dominant foundation. Its robust development and extension in the literature have focused on cognitive issues in actors' behaviors as a behavioral foundation of SM. Methodological issues in SM research have become dominant between 2004 and 2011, but their influence has been inconsistent. The authors concluded by recommending future directions to increase maturity in the SM research domain.Originality/valueThis is the first paper to elucidate the intellectual structure of SM by adopting the co-citation analysis through the social network analysis.


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