Network Analysis for Knowledge Flows of the Cosmetics Industry in South Korea

2021 ◽  
Vol 24 (3) ◽  
pp. 439-459
Author(s):  
Yewon Lee ◽  
Ilyoung Jung ◽  
Sula Jin ◽  
Kwang-ho Lee
Keyword(s):  
Network Analysis ◽  
South Korea ◽  
Knowledge Flows

Network Analysis for Knowledge Flows of the Cosmetics Industry in South Korea

2021 ◽  
Vol 24 (3) ◽  
pp. 439-459
Author(s):  
Yewon Lee ◽  
Ilyoung Jung ◽  
Sula Jin ◽  
Kwang-ho Lee
Keyword(s):  
Network Analysis ◽  
South Korea ◽  
Knowledge Flows

FinTech innovation and knowledge flows in Hong Kong’s financial sector: a social network analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anson Au
Keyword(s):  
Hong Kong ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Commercial Banks ◽  
Financial Sector ◽  
Knowledge Flows ◽  
Foreign Firms ◽  
Content Type ◽  
Network Position

Purpose This paper aims to examine how financial technology (FinTech) knowledge from foreign firms flows into and among elite commercial banks in Hong Kong’s financial sector to drive innovation. Design/methodology/approach Using social network analysis and regression analysis on a novel database of patents held by Hong Kong’s elite commercial banks, this paper examines the relationships between network position and FinTech knowledge flow. Findings This paper finds four untold patterns of innovation and inequality in Hong Kong’s financial sector: only three banks are responsible for all the FinTech knowledge entering Hong Kong; most foreign FinTech comes from the USA through Hong Kong and Shanghai Banking Corporation, whereas most FinTech from China enters through Fubon Bank and Development Bank of Singapore; older banks and banks with more connections to firms inside Asia are more likely to import FinTech; the most beneficial sources of FinTech for a bank’s network position are firms from outside Asia. Originality/value Despite the well-documented volumes of cross-border and cross-continental movement of financial institutions in Hong Kong, there is little work on the knowledge flows that underwrite this mobility. This paper addresses this gap by using FinTech knowledge flows to map the distribution of innovation, network position and competitive advantage in Hong Kong’s financial sector.

Network analysis of the tweets on South Korea–Japan conflict

2021 ◽  
pp. 69-86
Author(s):  
Dongwoo Lim ◽  
Fujio Toriumi ◽  
Kaori Hayashi
Keyword(s):  
Network Analysis ◽  
South Korea

scholarly journals Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea

10.2196/18897 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e18897 ◽  
Author(s):  
Han Woo Park ◽  
Sejung Park ◽  
Miyoung Chong
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Network Analysis ◽  
South Korea ◽  
Medical Information ◽  
Systematic Research ◽  
News Frames ◽  
Starting Point ◽  
Significant Difference

Background SARS-CoV-2 (severe acute respiratory coronavirus 2) was spreading rapidly in South Korea at the end of February 2020 following its initial outbreak in China, making Korea the new center of global attention. The role of social media amid the current coronavirus disease (COVID-19) pandemic has often been criticized, but little systematic research has been conducted on this issue. Social media functions as a convenient source of information in pandemic situations. Objective Few infodemiology studies have applied network analysis in conjunction with content analysis. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. The real time aggregation of social media data can serve as a starting point for designing strategic messages for health campaigns and establishing an effective communication system during this outbreak. Methods Korean COVID-19-related Twitter data were collected on February 29, 2020. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. We generated four networks in terms of key issues regarding COVID-19 in Korea. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. Next, we classified top news channels shared via tweets. Lastly, we conducted a content analysis of news frames used in the top-shared sources. Results The network analysis suggests that the spread of information was faster in the Coronavirus network than in the other networks (Corona19, Shincheon, and Daegu). People who used the word “Coronavirus” communicated more frequently with each other. The spread of information was faster, and the diameter value was lower than for those who used other terms. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers’ attention to the crisis. Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types. The news frames used in the top sources were similar across the networks (P=.89, 95% CI 0.004-0.006). Tweets containing medically framed news articles (mean 7.571, SD 1.988) were found to be more popular than tweets that included news articles adopting nonmedical frames (mean 5.060, SD 2.904; N=40, P=.03, 95% CI 0.169-4.852). Conclusions Most of the popular news on Twitter had nonmedical frames. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. Social media network analytics cannot replace the work of public health officials; however, monitoring public conversations and media news that propagates rapidly can assist public health professionals in their complex and fast-paced decision-making processes.

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