Social Network Analysis of “Clexa” Community Interaction Patterns

2019 ◽  
pp. 257-264 ◽  
Author(s):  
Kristina G. Kapanova ◽  
Velislava Stoykova
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Interaction Patterns ◽  
Community Interaction

New Technologies, New Horizons

2011 ◽  
pp. 23-41
Author(s):  
Hiller A. Spires ◽  
Meixun Zheng ◽  
Manning Pruden
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Graduate Students ◽  
Network Analysis ◽  
New Technologies ◽  
Interaction Patterns ◽  
Teaching With Technology ◽  
Graduate Course ◽  
Pedagogical Content ◽  
New Horizons

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.

scholarly journals Social Network Analysis to Examine Interaction Patterns in Knowledge Building Communities

2010 ◽  
Vol 36 (1) ◽  
Author(s):  
Donald N. Philip
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Building ◽  
Group Processes ◽  
Interaction Patterns ◽  
Face To Face ◽  
Grade 5 ◽  
Teachers And Students ◽  
Building Community

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.

scholarly journals Passing Network Analysis of Positional Attack Formations in Handball

2019 ◽  
Vol 70 (1) ◽  
pp. 209-221 ◽  
Author(s):  
Florian Korte ◽  
Martin Lames
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Suitable Method ◽  
Interaction Patterns ◽  
Optimal Position ◽  
Key Players ◽  
Sport Teams ◽  
The Individual ◽  
General Balance

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.

scholarly journals Association of Social Network Analysis with Mental Models in Emergency Management Teams

2019 ◽  
Author(s):  
Bjørn Sætrevik ◽  
Line Solheim Kvamme
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Emergency Management ◽  
Mental Models ◽  
Shared Mental Models ◽  
Management Teams ◽  
Interaction Patterns ◽  
Team Members ◽  
The Impact

Social network analysis is a preferred approach to examine the impact of social processes and mechanisms on team performance, but it can be challenging to measure these dynamics in applied settings. Our aim was to test whether the understanding of the task at hand was more accurate and more shared for teams with more evenly distributed interaction patterns. We pre-registered a novel approach for measuring social networks from sparse reporting of ranked interactions. Our sample was eleven emergency management teams that performed a scenario training exercise, where we asked factual questions about the ongoing task during performance, and retrospective questions about who were the most important communication and collaboration partners. We quantified shared mental models as the extent to which a team member showed the same understanding as the rest of their team, and quantified situation awareness as the extent to which team members showed the same knowledge as their team leader. We calculated which team members where most central to the network, and which networks had more evenly distributed networks. Our findings support the pre-registered hypotheses that more interconnected teams are associated with more accurate and more shared mental models, while the individual’s position in the network was not associated with MM.

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
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Type I ◽  
Interaction Patterns ◽  
Health Crisis ◽  
Interactive Governance ◽  
Governance Systems ◽  
Multi Level ◽  
Definition Of

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.

scholarly journals Extracting Medical Insights and Policy Implications to Manage Irritable Bowel Syndrome from Online Posts of Adolescents and Parents (Preprint)

2020 ◽  
Author(s):  
Bu Zhong ◽  
Qian Liu
Keyword(s):  
Irritable Bowel Syndrome ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
School Performance ◽  
Gastrointestinal Symptoms ◽  
Policy Implications ◽  
Childhood And Adolescence ◽  
Interaction Patterns ◽  
Irritable Bowel

BACKGROUND The existing research on adolescents’ irritable bowel syndrome (IBS) is helpful towards understanding the pathophysiology of the disease, and the etiology of abdominal functional pain, food induced gastrointestinal symptoms, and other dietary consequences. But not much is known about complications that arise from the symptoms and everyday management of IBS among childhood and adolescence. OBJECTIVE As adolescents with IBS are increasingly sharing information about their symptoms in online healthcare forums, this study aims to analyze their posts and those from their parents and discover medical insights that can be used by doctors, patients, and caregivers to manage IBS symptoms in adolescents. METHODS After mining the longitudinal data from IBSgroup.org, we analyzed all the posts (over 750 topics and 3400 replies) from adolescents with IBS aged 13-17 and parents having children with IBS in the IBSgroup.org forum. We first detect six main topics each for both parents’ posts and teens’ posts. Then a social network analysis was performed to gain insights on the nature of the patients’ online interaction patterns. RESULTS Both the adolescents and parents gain social support from the online platform. While parents are more anxious about the pathology of IBS, the adolescents worry more about its effect on their everyday activities and social lives. Topic modeling shows that IBS affects teens most in the areas of pain and school performance. Further, the issues raised by parents suggest that girls be bothered more by school performance over pain, while boys show exactly the opposite – pain is of greater concern than school performance. CONCLUSIONS The study is the first attempt to leverage machine learning approaches and social network analysis to find top IBS concerns from the perspectives of children, adolescents and caregivers. Adolescents with IBS suffer physical pain and are deeply disturbed by social influences and anxiety due to the symptoms. Boys and girls are affected differently by pain and school performance, whose views on the effects differ from parents’.

scholarly journals A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit (ANT) R package

2018 ◽  
Author(s):  
Sosa Sebastian ◽  
Puga-Gonzalez Ivan ◽  
Hu Feng He ◽  
Zhang Peng ◽  
Xiaohua Xie ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
R Package ◽  
Interaction Patterns ◽  
Network Properties ◽  
New Methodologies ◽  
The Many ◽  
Animal Social Networks

AbstractHow animals interact and develop social relationships regarding, individual attributes, sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis, allow us to elucidate these types of questions. However, the different methodologies developed to that end and the speed at which they emerge make their use difficult. Moreover, the lack of communication between the different software developed to provide an answer to the same/different research questions is a source of confusion. The R package Animal Network Toolkit (ANT) was developed with the aim of implementing in one package the many different social network analysis techniques currently used in the study of animal social networks. Hence, ANT is a toolkit for animal research allowing among other things to: 1) measure global, dyadic and nodal networks metrics; 2) perform data randomization: pre-network and network (node and link) permutations; 3) perform statistical permutation tests. The package is partially coded in C++ for an optimal coding speed, and it gives researchers a workflow from raw data to the achievement of statistical analyses, allowing for a multilevel approach: from individual position and role within the network, to the identification of interaction patterns, and the analysis of the overall network properties.

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