Interactive Governance Between and Within Governmental Levels and Functions: A Social Network Analysis of China's Case Against COVID-19

2021 ◽  
pp. 027507402110595
Author(s):  
Dongmin Yao ◽  
Jing Li ◽  
Yijing Chen ◽  
Qiunan Gao ◽  
Wenhong Yan

COVID-19 has created long-lasting yet unprecedented challenges worldwide. In addition to scientific efforts, political efforts and public administration are also crucial to contain the disease. Therefore, understanding how multi-level governance systems respond to this public health crisis is vital to combat COVID-19. This study focuses on China and applies social network analysis to illustrate interactive governance between and within levels and functions of government, confirming and extending the existing Type I and Type II definition of multi-level governance theory. We characterize four interaction patterns—vertical, inter-functional, intra-functional, and hybrid—with the dominant pattern differing across governmental functions and evolving as the pandemic progressed. Empirical results reveal that financial departments of different levels of government interact through the vertical pattern. At the same time, intra-functional interaction also exists in provincial financial departments. The supervision departments typically adopt the inter-functional pattern at all levels. At the cross-level and cross-function aspects, the hybrid interaction pattern prevails in the medical function and plays a fair part in the security, welfare, and economic function. This study is one of the first to summarize the interaction patterns in a multi-level setting, providing practical implications for which pattern should be applied to which governmental levels/functions under what pandemic condition.

Author(s):  
Anu Taneja ◽  
Bhawna Gupta ◽  
Anuja Arora

The enormous growth and dynamic nature of online social networks have emerged to new research directions that examine the social network analysis mechanisms. In this chapter, the authors have explored a novel technique of recommendation for social media and used well known social network analysis (SNA) mechanisms-link prediction. The initial impetus of this chapter is to provide general description, formal definition of the problem, its applications, state-of-art of various link prediction approaches in social media networks. Further, an experimental evaluation has been made to inspect the role of link prediction in real environment by employing basic common neighbor link prediction approach on IMDb data. To improve performance, weighted common neighbor link prediction (WCNLP) approach has been proposed. This exploits the prediction features to predict new links among users of IMDb. The evaluation shows how the inclusion of weight among the nodes offers high link prediction performance and opens further research directions.


Author(s):  
Hiller A. Spires ◽  
Meixun Zheng ◽  
Manning Pruden

The purpose of this chapter is to present graduate students’ views of their Technological Pedagogical Content Knowledge (TPACK) development. These graduate students are also teachers. Data was collected using a mixed method approach founded on the TPACK Framework and social network analysis. Koehler and Mishra (2006) claim that effective teaching with technology requires TPACK, or an ability to integrate content, pedagogy and technology flexibly during the act of teaching. As part of a graduate course on new literacies and media, participants were required to design and implement lessons that incorporated a range of technologies, produce written reflections about their experiences, and engage in online interactions with participants in the class. Qualitative results from participants’ written reflections revealed four themes relative to TPACK. Additionally, a social network analysis demonstrated a positive relationship between participants’ views on their TPACK development and their interaction patterns within the online learning environment. This study shows that the TPACK framework can be a useful tool, giving educators a productive way to think about technology integration as they navigate the rapid changes prompted by emerging technologies.


Author(s):  
Donald N. Philip

This paper describes use of social network analysis to examine student interaction patterns in a Grade 5/6 Knowledge Building class. The analysis included face-to-face interactions and interactions in the Knowledge Forum® Knowledge Building environment. It is argued that sociogram data are useful to reveal group processes; in sociological terms, the community lies in the connections among the group. A classroom of unconnected individuals is unlikely to form as a Knowledge Building community; data analyses reported in this study show promise in understanding the dynamics of Knowledge Building in a consistent and measurable way. The strength of the work is not in particular patterns demonstrated but in new forms of assessment and their potential to inform work as it proceeds. The research reported shows that teachers and students are finding social network analysis useful and that through their engagement research-practitioner-engineer teams are better positioned to develop tools to advance Knowledge Building pedagogy.


2019 ◽  
Vol 70 (1) ◽  
pp. 209-221 ◽  
Author(s):  
Florian Korte ◽  
Martin Lames

Abstract The aim of this study was to characterize handball from a social network analysis perspective by analyzing 22 professional matches from the 2018 European Men's Handball Championship. Social network analysis has proven successful in the study of sports dynamics to investigate the interaction patterns of sport teams and the individual involvement of players. In handball, passing is crucial to establish an optimal position for throwing the ball into the goal of the opponent team. Moreover, different tactical formations are played during a game, often induced by two-minute suspensions or the addition of an offensive player replacing the goalkeeper as allowed by the International Handball Federation since 2016. Therefore, studying the interaction patterns of handball teams considering the different playing positions under various attack formations contributes to the tactical understanding of the sport. Degree and flow centrality as well as density and centralization values were computed. As a result, quantification of the contribution of individual players to the overall organization was achieved alongside the general balance in interplay. We identified the backcourt as the key players to structure interplay across tactical formations. While attack units without a goalkeeper were played longer, they were either more intensively structured around back positions (7 vs. 6) or spread out (5 + 1 vs. 6). We also found significant differences in the involvement of wing players across formations. The additional pivot in the 7 vs. 6 formation was mostly used to create space for back players and was less involved in interplay. Social network analysis turned out as a suitable method to govern and quantify team dynamics in handball.


Author(s):  
Hirotoshi Takeda ◽  
Duane P. Truex ◽  
Michael J. Cuellar ◽  
Richard Vidgen

Following previous research findings, this paper argues that the currently predominant method of evaluating scholar performance - publication counts in “quality” journals - is flawed due to the subjectivity inherent in the generation of the list of approved journals and absence of a definition of quality. Truex, Cuellar, and Takeda (2009) improved on this method by substituting a measurement of “influence” using the Hirsch statistics to measure ideational influence. Since the h-family statistics are a measure of productivity and the uptake of a scholar’s ideas expressed in publications, this methodology privileges the uptake of a scholar’s ideas over the venue of publication. Influence is built through other means than by having one’s papers read and cited. The interaction between scholars resulting in co-authored papers is another way to build scholarly influence. This aspect of scholarly influence, which the authors term social influence, can be assessed by Social Network Analysis (SNA) metrics that examine the nature and strength of coauthoring networks among IS Scholars. The paper demonstrates the method of assessing social influence by analysis of the social network of AMCIS scholars and compares the results of this analysis with other co-authorship networks from the ECIS and ICIS communities.


2018 ◽  
Vol 78 ◽  
pp. 420-429 ◽  
Author(s):  
Tolera Senbeto Jiren ◽  
Arvid Bergsten ◽  
Ine Dorresteijn ◽  
Neil French Collier ◽  
Julia Leventon ◽  
...  

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