Network Analysis of the US–China Hegemonic Transition

2020 ◽  
Author(s):  
Yeongkyun Jang ◽  
Jae-Suk Yang

2020 ◽  
Vol 540 ◽  
pp. 123064 ◽  
Author(s):  
Rangan Gupta ◽  
Chi-Keung (Marco) Lau ◽  
Xin Sheng


2020 ◽  
Vol 110 (5) ◽  
pp. 718-724 ◽  
Author(s):  
Dror Walter ◽  
Yotam Ophir ◽  
Kathleen Hall Jamieson

Objectives. To understand how Twitter accounts operated by the Russian Internet Research Agency (IRA) discussed vaccines to increase the credibility of their manufactured personas. Methods. We analyzed 2.82 million tweets published by 2689 IRA accounts between 2015 and 2017. Combining unsupervised machine learning and network analysis to identify “thematic personas” (i.e., accounts that consistently share the same topics), we analyzed the ways in which each discussed vaccines. Results. We found differences in volume and valence of vaccine-related tweets among 9 thematic personas. Pro-Trump personas were more likely to express antivaccine sentiment. Anti-Trump personas expressed support for vaccination. Others offered a balanced valence, talked about vaccines neutrally, or did not tweet about vaccines. Conclusions. IRA-operated accounts discussed vaccines in manners consistent with fabricated US identities. Public Health Implications. IRA accounts discussed vaccines online in ways that evoked political identities. This could exacerbate recently emerging partisan gaps relating to vaccine misinformation, as differently valenced messages were targeted at different segments of the US public. These sophisticated targeting efforts, if repeated and increased in reach, could reduce vaccination rates and magnify health disparities.



2019 ◽  
Vol 69 (5) ◽  
pp. 467-489 ◽  
Author(s):  
Yee Man Margaret Ng ◽  
Harsh Taneja

Abstract With half the world now online, a handful of websites dominate globally. Yet little is known about the homogeneity or geographical distinctness of global web use patterns. Focusing beyond popular sites, we inquired into how and why countries are similar in their web use patterns, developing a framework drawing on the literatures on media globalization, as well as Internet geographies. To compute similarities in web use between countries, we utilized an algorithm that considered both ranking positions and overlap counts on ranked lists of the 100 most popular websites for 174 countries, totaling 6,252 unique websites. Findings from a network analysis and from regressions suggest that countries with similar languages and shared borders, as well as those vastly different in their Internet market sizes, tend to have similar web use patterns. Neither are countries particularly similar to the US in web use nor does the prevalence of English speakers have an influence.



2013 ◽  
Vol 31 (6) ◽  
pp. 568-579 ◽  
Author(s):  
Rayyan Alsamadani ◽  
Matthew Hallowell ◽  
Amy Nicole Javernick-Will


2022 ◽  
Author(s):  
Margherita Russo ◽  
◽  
Fabrizio Alboni ◽  
Jorge Carreto Sanginés ◽  
Manlio De Domenico ◽  
...  

In 2018, after 25 years of the North America Trade Agreement (NAFTA), the United States requested new rules which, among other requirements, increased the regional con-tent in the production of automotive components and parts traded between the three part-ner countries, United States, Canada and Mexico. Signed by all three countries, the new trade agreement, USMCA, is to go into force in 2022. Nonetheless, after the 2020 Presi-dential election, the new treaty's future is under discussion, and its impact on the automo-tive industry is not entirely defined. Another significant shift in this industry – the acceler-ated rise of electric vehicles – also occurred in 2020: while the COVID-19 pandemic largely halted most plants in the automotive value chain all over the world, at the reopen-ing, the tide is now running against internal combustion engine vehicles, at least in the an-nouncements and in some large investments planned in Europe, Asia and the US. The definition of the pre-pandemic situation is a very helpful starting point for the analysis of the possible repercussions of the technological and geo-political transition, which has been accelerated by the epidemic, on geographical clusters and sectorial special-isations of the main regions and countries. This paper analyses the trade networks emerg-ing in the past 25 years in a new analytical framework. In the economic literature on inter-national trade, the study of the automotive global value chains has been addressed by us-ing network analysis, focusing on the centrality of geographical regions and countries while largely overlooking the contribution of countries' bilateral trading in components and parts as structuring forces of the subnetwork of countries and their specific position in the overall trade network. The paper focuses on such subnetworks as meso-level structures emerging in trade network over the last 25 years. Using the Infomap multilayer clustering algorithm, we are able to identify clusters of countries and their specific trades in the automotive internation-al trade network and to highlight the relative importance of each cluster, the interconnec-tions between them, and the contribution of countries and of components and parts in the clusters. We draw the data from the UN Comtrade database of directed export and import flows of 30 automotive components and parts among 42 countries (accounting for 98% of world trade flows of those items). The paper highlights the changes that occurred over 25 years in the geography of the trade relations, with particular with regard to denser and more hierarchical network gener-ated by Germany’s trade relations within EU countries and by the US preferential trade agreements with Canada and Mexico, and the upsurge of China. With a similar overall va-riety of traded components and parts within the main clusters (dominated respectively by Germany, US and Japan-China), the Infomap multilayer analysis singles out which com-ponents and parts determined the relative positions of countries in the various clusters and the changes over time in the relative positions of countries and their specialisations in mul-tilateral trades. Connections between clusters increase over time, while the relative im-portance of the main clusters and of some individual countries change significantly. The focus on US and Mexico and on Germany and Central Eastern European countries (Czech Republic, Hungary, Poland, Slovakia) will drive the comparative analysis.



2021 ◽  
pp. 000276422110562
Author(s):  
Sohana Nasrin ◽  
Dana R. Fisher

How does collective identity form in virtual spaces and what role do hashtags play? This paper takes advantage of a unique dataset that includes surveys from activists who organized the nationally coordinated climate strikes in the US that began in spring 2019 to answer these questions. Building on the research about collective identity formation online and the role that hashtags play, we employ social network analysis to assess how collective identity forms online over three waves of protests. In particular, we analyze how activists involved in the youth climate movement used hashtags to project their collective identities and create collective narratives. Our findings show how hashtags use varied over the period of our study, in some cases indicating the formation of a thin collective identity. They also show that there are patterns in the ways hashtags are employed by activists in the movement that suggest the formation of subaltern narratives among those affiliated with youth-led groups. Our paper concludes by considering how this finding helps us understand collective identity in virtual spaces and the role that hashtags play more specifically within social movements.



Author(s):  
Elie Ngomseu Mambou ◽  
Samuel Nlend ◽  
Harold Liu


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Haotian Hu ◽  
Dongbo Wang ◽  
Sanhong Deng

AbstractPurposeThis study aims to explore the trend and status of international collaboration in the field of artificial intelligence (AI) and to understand the hot topics, core groups, and major collaboration patterns in global AI research.Design/methodology/approachWe selected 38,224 papers in the field of AI from 1985 to 2019 in the core collection database of Web of Science (WoS) and studied international collaboration from the perspectives of authors, institutions, and countries through bibliometric analysis and social network analysis.FindingsThe bibliometric results show that in the field of AI, the number of published papers is increasing every year, and 84.8% of them are cooperative papers. Collaboration with more than three authors, collaboration between two countries and collaboration within institutions are the three main levels of collaboration patterns. Through social network analysis, this study found that the US, the UK, France, and Spain led global collaboration research in the field of AI at the country level, while Vietnam, Saudi Arabia, and United Arab Emirates had a high degree of international participation. Collaboration at the institution level reflects obvious regional and economic characteristics. There are the Developing Countries Institution Collaboration Group led by Iran, China, and Vietnam, as well as the Developed Countries Institution Collaboration Group led by the US, Canada, the UK. Also, the Chinese Academy of Sciences (China) plays an important, pivotal role in connecting the these institutional collaboration groups.Research limitationsFirst, participant contributions in international collaboration may have varied, but in our research they are viewed equally when building collaboration networks. Second, although the edge weight in the collaboration network is considered, it is only used to help reduce the network and does not reflect the strength of collaboration.Practical implicationsThe findings fill the current shortage of research on international collaboration in AI. They will help inform scientists and policy makers about the future of AI research.Originality/valueThis work is the longest to date regarding international collaboration in the field of AI. This research explores the evolution, future trends, and major collaboration patterns of international collaboration in the field of AI over the past 35 years. It also reveals the leading countries, core groups, and characteristics of collaboration in the field of AI.



2021 ◽  
Vol 9 (2) ◽  
pp. 112-123 ◽  
Author(s):  
Dana R. Fisher ◽  
Sohana Nasrin

How has the youth climate movement in the US grown since the Climate Strikes began and in what ways did it change as it grew? This article takes advantage of a unique dataset that includes surveys from activists who organized the nationally coordinated climate strikes in the US that began with Fridays for Future in spring 2019. Building on the research on alliance building and strategic coalitions, this article analyzes how the patterns of participation changed over the period of the study. We employ social network analysis to map the affiliation networks among the organizers of these events to assess the coalitions of groups involved and the shifting organizational landscape. Our analysis does not provide evidence that groups spanned the boundaries across movements, nor does it show that identity plays a role in coalition building in this movement. Instead, by mapping out the coalition of organizations within this movement and how connections among them change over time, we see clear evidence that this youth-led movement was reoriented by adult-led organizations. Our article concludes by considering how these findings suggest the future trajectory of the youth climate movement and its role in a ‘new climate politics’ in America.



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