Network analysis of the tweets on South Korea–Japan conflict

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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The scientific and technological interdisciplinary research of government research institutes: network analysis of the innovation cluster in South Korea

Policy Studies ◽

10.1080/01442872.2019.1593343 ◽

2019 ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Yoonjung Jung ◽

Euiseok Kim ◽

Wonjoon Kim

Keyword(s):

Network Analysis ◽

South Korea ◽

Interdisciplinary Research ◽

Innovation Cluster ◽

Research Institutes ◽

Government Research

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Tweeting about abusive comments and misogyny in South Korea following the suicide of Sulli, a female K-pop star: Social and semantic network analyses

El profesional de la información ◽

10.3145/epi.2021.sep.05 ◽

2021 ◽

Author(s):

Sejung Park ◽

Jiwon Kim

Keyword(s):

Social Network ◽

Network Analysis ◽

South Korea ◽

Hate Speech ◽

Social Issues ◽

Semantic Network ◽

News Coverage ◽

Public Discussion ◽

The Public ◽

Network Analyses

This study examined the development of the public discussion on Twitter about the abusive comments specific to misogynistic discourse after the suicide of Sulli, a female celebrity in South Korea. Both the pattern of social networking between the users and the semantic representations of user responses were analyzed from a social network perspective using a large-scale Twitter dataset. A total of 37,101 tweets generated by 25,258 users were collected and analyzed. The findings of the network analysis suggest that hubs and authorities on Twitter were closely connected to each other and contributed to promoting the public discussion about abusive comments in response to her death. The results of the semantic network analysis suggested that her death, presumably due in part to continuous hateful comments from trolls, evoked an open discussion about the deeply rooted abusive comments and misogyny that are prevalent in South Korea. Users perceived that sensational news coverage about celebrities and unethical journalistic practices led to abusive comments and her death. The users shared their observations that gendered hate speech contributed to Sulli’s bullying. Dominant words that referred to Sulli’s sexual harassment show the ways in which haters had bullied her, as well as the criticism of online harassment. The results imply that the issue of online misogyny was closely associated with abusive comments in the public consciousness. This study verified the role of celebrities in increasing awareness about social issues and word-of-mouth dissemination even after a death. This study also offers methodological insights by demonstrating how social network analysis can be used to analyze public discussion using big data.

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Technology Fusion Characteristics in the Solar Photovoltaic Industry of South Korea: A Patent Network Analysis Using IPC Co-Occurrence

Sustainability ◽

10.3390/su12219084 ◽

2020 ◽

Vol 12 (21) ◽

pp. 9084

Author(s):

Sungho Son ◽

Nam-Wook Cho

Keyword(s):

Network Analysis ◽

South Korea ◽

New Technologies ◽

Early Stage ◽

Solar Photovoltaic ◽

International Patent Classification ◽

Structural Pattern ◽

Patent Classification ◽

International Patent ◽

Key Technologies

This study analyzes the technology fusion phenomena and its characteristics, focusing on the solar photovoltaic (PV) industry in South Korea. Co-occurrence networks of international patent classification (IPC) codes have been analyzed based on the photovoltaic patents in South Korea during a 15-year period (2002–2016). The results reveal that, while the strength of technology fusion has greatly increased during the period, the structural pattern of fusion has been diversified or decentralized. In the early stage, widespread emergence of new technologies has been observed but, in the later stage, the focus of fusion shifted to the utilization of existing technologies. The characteristics of key technologies also changed as the technology fusion progressed. In the early stage, product technologies such as materials and components played a central role, while operation technologies such as monitor, structure, and arrangement were the drivers of fusion during the later stage.

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