Strategizing Marriage: A Genealogical Analysis of Korean Marriage Networks

2017 ◽  
Vol 48 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Sangkuk Lee ◽  
Wonjae Lee
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Fifteenth Century ◽  
Korean History ◽  
Political Status ◽  
Genealogical Analysis ◽  
Medieval Korea ◽  
Insight Into

The genealogy of the Andong Gwon-ssi in the Seongwha period—the oldest extant genealogy in Korean history—offers a unique opportunity to explore political changes and gain insight into the formation of inner circles in Korea during the thirteenth to fifteenth century. Social-network analysis of the marriage networks within this genealogy reveals that for elite families in medieval Korea, marital strategy was as important as ancestry to the maintenance of social/political status.

scholarly journals Improvised Music in Berlin 2012-13: A Brief Ethnographic Portrait

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Tom Arthurs
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Structure ◽  
Point Of View ◽  
Music Making ◽  
Improvised Music ◽  
Phd Thesis ◽  
Point Of Departure ◽  
Insight Into

This paper uses approaches from ethnography and Social Network Analysis to provide a brief insight into the practical, economic and social structure of Berlin’s Improvised Music scene during 2012 and 2013. The findings presented here address imbalances of gender and race, and highlight the (often difficult) financial reality of a life in Improvised Music. Audience, venues and performers are portrayed in order to provide an entry point for those unfamiliar with Improvised Music communities, and to offer an empirically researched point of departure for those already acquainted with such musicians and practices. This paper is an adaptation of parts of my PhD thesis “The Secret Gardeners: An Ethnography of Improvised Music in Berlin (2012-13),” which addresses the aesthetics, ideologies and practicalities of contemporary European Improvised Music-making from the point of view of 34 key practitioners and “expert” listeners.

scholarly journals Using Google Maps to Show the Pattern of International Co-Author Collaboration in Pharmaceutics

2018 ◽  
pp. 1-9
Keyword(s):  
Drug Delivery ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Graphical Representations ◽  
Deep Insight ◽  
Microsoft Excel ◽  
Google Maps ◽  
Future Studies ◽  
Insight Into

Objective: To understand international co-author collaboration in pharmaceutics and to visualize results by Google maps and social network analysis (SNA). Methods: Selecting 311 abstracts from the Medline based on keyword pharmaceutics [journal], we reported following features of pharmaceutics: (1) nation distribution across continents; (2) main keywords frequently displayed in papers; (3) the eminent author in pharmaceutics. We programmed Microsoft Excel VBA for extracting data from Medline. Google Maps and SNA Pajek software show graphical representations of pharmaceutics. Results: We found that (1) the most number of papers in nations are from U.S.(81, 16.05%) and Japan(34, 10.93%); (2) the most linked keywords are Pharmacokinetics and drug delivery; (3) the eminent authors are Muhammad Sohail Arshad(UK) and Takeshi Yokoo(Japan). Conclusion: Social network analysis provides wide and deep insight into relationships of entities we interested. The results drawn from Google maps can provide more information to future studies in academics.

Dynamic Social Network Mining

2013 ◽  
pp. 122-144
Author(s):  
Luca Cagliero ◽  
Alessandro Fiori
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Discovery ◽  
Network Mining ◽  
Social Network Mining ◽  
Dynamic Social Network ◽  
Main Work ◽  
Insight Into

This Chapter overviews most recent data mining approaches proposed in the context of social network analysis. In particular, it aims at classifying the proposed approaches based on both the adopted mining strategies and their suitability for supporting knowledge discovery in a dynamic context. To provide a thorough insight into the proposed approaches, main work issues and prospects in dynamic social network analysis are also outlined.

scholarly journals Topology of the World Tourism Web

2021 ◽  
Vol 11 (5) ◽  
pp. 2253
Author(s):  
Katarina Kostelić ◽  
Marko Turk
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Biological Network ◽  
The World ◽  
Source Countries ◽  
And Diffusion ◽  
Insight Into ◽  
Diffusion Properties

The applications of social network analysis to the world tourism network are scarce, and a research update is long overdue. The goal of this research is to examine the topology of the world tourism network and to discuss the meaning of its characteristics in light of the current situation. The data used for the analysis comprise 193 target countries, 242 source countries, and 17,022 links, which is an overall 1,448,285,894 travels in 2018. Social network analysis is applied to the data to determine network topological and diffusion properties, as well as the network structure and its regularities (does it behave more as a social or a technological/biological network?). While results presented in this paper give a thorough insight into the world tourism network in the year 2018, they are only a glimpse in comparison to the possibilities for further research.

A Data Visualization Dashboard like a Game to Show Associations Between Cited-by and Similar Journals related to JMIR Serious Games: A Bibliometric Study (Preprint)

2018 ◽  
Author(s):  
Tsair-Wei Chien ◽  
Hsien-Yi Wang ◽  
Yang Shao ◽  
Willy Chou
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Serious Games ◽  
Deep Insight ◽  
The Past ◽  
The Given ◽  
Strength Of Association ◽  
Insight Into ◽  
The U.S

BACKGROUND Over 47,703 articles were found on Pubmed.com by searching for the keyword “association between[Title]” in the past. However, to date, none present the association between cited-by and similar journals related to a given journal. Authors need one effective and efficient way to find journals related to a specific journal. The strength of association between cited-by and similar journals for a given journal is required to report. OBJECTIVE This study aims (1) to present the feature of a given journal about their keyword topics and international author collaborations; (2) to show the cited-by and similar journals related to the given journal; (3) to investigate the association between their cited-by and similar journals. METHODS We obtained 85 abstracts since 2013 from Medline based on the keywords of ("JMIR Serious Games[Journal]) on June 30, 2018, and plotted the clusters, including (i) international author collaborations, (ii) keyword topics, (iii)cited-by and similar journals related to JMIR Serious Games(JSG), and (iv) association between cited-by and similar journals, on Google Maps by using social network analysis(SNA). RESULTS This study found that (1) the most number of papers are from the U.S.( 28, 32.9%) and the U.K. (11,12.9 %), the most frequently used keywords are serious games and video games; (2) the top two journals for cited-by and similar journals, respectively, are (i) JMIR mHealth uHealth(IF=4.541), J Med Internet Res (IF=4.671) and (ii) Games Health J (IF= 2.019), J Med Internet Res (IF=4.671); (3) a mild association(=0.14) exists between cited-by and similar journals related to JSG. CONCLUSIONS SNA provides deep insight into the relationships of related journals to a given journal. The results of this research can provide readers with a knowledge and concept diagram to use with future manuscript submissions to JSG. CLINICALTRIAL Not available

scholarly journals Listed Buildings as Socio-material Hybrids: Assessing Tangible and Intangible Heritage Using Social Network Analysis

2020 ◽  
Vol 5 (2) ◽  
pp. 169-190
Author(s):  
Johnathan Djabarouti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Phenomena ◽  
Methodist Church ◽  
Built Heritage ◽  
Intangible Heritage ◽  
Grade Ii ◽  
Insight Into ◽  
Inherent Part

Immaterial manifestations of culture have received increasing attention over the past two decades. This is of particular relevance to the contemporary built heritage professional who must not only consider intangible heritage within assessments but attempt to understand its relationship with the physical building fabric. Underpinned by a ‘Practice Theory’ ontology, this research explores how social network analysis (SNA) can reveal entanglements between tangible and intangible heritage by focussing on practices and relationships. Using the Grade II* Long Street Methodist Church and Sunday School, Greater Manchester, UK, the study demonstrates how the basic use of SNA for built heritage assessment can offer a deeper insight into the significance of a listed building. The study demonstrates how SNA can support: an equality of visibility across heritage domains, a better understanding of tangible–intangible relationships and the illumination of underlying practices that sustains these relationships. Perhaps most importantly, it emphasizes the dynamic and unpredictable nature of heritage by de-emphasizing the centrality of the building within heritage assessment processes and reconceptualizing it as an inherent part of social phenomena. In doing so, it suggests one must accept the notion that socio-material practices should be considered for conservation and safeguarding, alongside the physical building itself.

scholarly journals How Learners Participate in Connectivist Learning: An Analysis of the Interaction Traces From a cMOOC

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Zhijun Wang ◽  
Terry Anderson ◽  
Li Chen
Keyword(s):  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The Social ◽  
Data Output ◽  
Participation Inequality ◽  
Interaction Traces ◽  
Insight Into ◽  
Interpretative Research

<p class="3">In this research paper, the authors analyse the collected data output during a 36 week cMOOC. Six-week data streams from blogs, Twitter, a Facebook group, and video conferences were tracked from the daily newsletter and the MOOCs’ hashtag (#Change 11). This data was analysed using content analysis and social network analysis within an interpretative research paradigm. The content analysis was used to examine the technology learners used to support their learning while the social network analysis focused on the participant in different spaces and their participation patterns in connectivist learning.</p><p class="3">The findings from this research include: 1) A variety of technologies were used by learners to support their learning in this course; 2) Four types of participation patterns were reveled, including unconnected floaters, connected lurkers, connected participants, and active contributors. The participation of learners displays the participation inequality typical of social media, but the ratio of active contributors is much higher than xMOOCs; 3) There were five basic structures of social networks formed in the learning; and 4) The interaction around topics and topic generation supports the idea of learning as network creation after the analysis of participation patterns that are based on some deep interactive topic. The aim of this study is to gain insight into the behaviors of learners in a cMOOC in an open and distributed online environment, so that future MOOCs designers and facilitators can understand, design and facilitate more effective MOOCs for learners.</p>

scholarly journals Empiricism and Theorizing in Epidemiology and Social Network Analysis

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Richard Rothenberg ◽  
Elizabeth Costenbader
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Empirical Data ◽  
Transmission Dynamics ◽  
Scientific Creativity ◽  
New Information ◽  
Testing Theory ◽  
The Relationship ◽  
Insight Into

The connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induction (generating theory from data) and deduction (testing theory with data). Einstein, in the 1920s, placed scientific creativity in that space. In the field of social network analysis, some remarkable theory has been developed, accompanied by sophisticated tools to develop, extend, and test the theory. At the same time, important empirical data have been generated that provide insight into transmission dynamics. Unfortunately, the connection between them is often tenuous and the iterative loop is frayed. This circumstance may arise both from data deficiencies and from the ease with which data can be created by simulation. But for whatever reason, theory and empirical data often occupy different orbits. Fortunately, the relationship, while frayed, is not broken, to which several recent analyses merging theory and extant data will attest. Their further rapprochement in the field of social network analysis could provide the field with a more creative approach to experimentation and inference.

Social network analysis of an emerging innovation: direct-to-garment printing technology

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yanan Yu ◽  
Marguerite Moore ◽  
Lisa P. Chapman
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Computational Technique ◽  
Fashion Industry ◽  
Printing Technology ◽  
Content Type ◽  
Context Specific ◽  
Insight Into

PurposeThe study primarily aims to examine an emerging fashion technology, direct-to-garment (DTG) printing, using data mining-driven social network analysis (SNA). Simultaneously, the study also demonstrates application of a group novel computational technique to capture, analyze and visually depict data for strategic insight into the fashion industry.Design/methodology/approachA total of 5,060 tweets related to DTG were captured using Crimson Hexagon. Python and Gephi were applied to convert, calculate and visualize the yearly networks for 2016–2019. Based on graph theory, degree centrality and betweenness centrality indices guide interpretation of the outcome networks.FindingsThe findings reveal insights into DTG printing technology networks through identification of interrelated indicators (i.e. nodes, edges and communities) over time. Deeper interpretation of the dominant indicators and the unique changes within each of the DTG communities were investigated and discussed.Practical implicationsThree SNA models suggest directions including the dominant apparel categories for DTG application, competing alternatives for apparel decorating approaches to DTG and growing market niches for DTG. Interpretation of the yearly networks suggests evolution of this domain over the investigation period.Originality/valueThe social media based, data mining-driven SNA method provides a novel path and a powerful technique for scholars and practitioners to investigate information among complex, abstract or novel topics such as DTG. Context specific findings provide initial insight into the evolving competitive structures driving DTG in the fashion market.

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