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Tyler Prochnow, Haley Delgado, Megan S. Patterson and M. Renée Umstattd Meyer

analysis is needed to determine and understand the effects of particular relationships and connections. The potential effects of these relationships can be examined by using social network analysis (SNA). 13 The SNA is a set of theories and methodologies designed to help researchers understand the social

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Heidi A. Wayment, Ann H. Huffman, Monica Lininger and Patrick C. Doyle

Key Points ▸ This study used social network analysis (SNA) to examine relationships between social structure, identity perceptions, and concussion-reporting support in an NCAA Division I football team. ▸ Team belonging was positively correlated with having more friends and being highly connected

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Ross C. Brownson, Diana C. Parra, Marsela Dauti, Jenine K. Harris, Pedro C. Hallal, Christine Hoehner, Deborah Carvalho Malta, Rodrigo S. Reis, Luiz Roberto Ramos, Isabela C. Ribeiro, Jesus Soares and Michael Pratt

Background:

Physical inactivity is a significant public health problem in Brazil that may be addressed by partnerships and networks. In conjunction with Project GUIA (Guide for Useful Interventions for Physical Activity in Brazil and Latin America), the aim of this study was to conduct a social network analysis of physical activity in Brazil.

Methods:

An online survey was completed by 28 of 35 organizations contacted from December 2008 through March 2009. Network analytic methods examined measures of collaboration, importance, leadership, and attributes of the respondent and organization.

Results:

Leadership nominations for organizations studied ranged from 0 to 23. Positive predictors of collaboration included: south region, GUIA membership, years working in physical activity, and research, education, and promotion/practice areas of physical activity. The most frequently reported barrier to collaboration was bureaucracy.

Conclusion:

Social network analysis identified factors that are likely to improve collaboration among organizations in Brazil.

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Megan S. Patterson and Patricia Goodson

Background:

Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people.

Methods:

SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET.

Results:

QAP regression analysis revealed a statistically significant model (R 2 = .375, P < .0001) predicting compulsive exercise behavior. Physical activity, body dissatisfaction, and network variables were statistically significant predictor variables in the QAP regression model.

Discussion:

In our sample, women who are connected to “important” or “powerful” people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

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Katrien Fransen, Stef Van Puyenbroeck, Todd M. Loughead, Norbert Vanbeselaere, Bert De Cuyper, Gert Vande Broek and Filip Boen

This research aimed to introduce social network analysis as a novel technique in sports teams to identify the attributes of high-quality athlete leadership, both at the individual and at the team level. Study 1 included 25 sports teams (N = 308 athletes) and focused on athletes’ general leadership quality. Study 2 comprised 21 sports teams (N = 267 athletes) and focused on athletes’ specific leadership quality as a task, motivational, social, and external leader. The extent to which athletes felt connected with their leader proved to be most predictive for athletes’ perceptions of that leader’s quality on each leadership role. Also at the team level, teams with higher athlete leadership quality were more strongly connected. We conclude that social network analysis constitutes a valuable tool to provide more insight in the attributes of high-quality leadership both at the individual and at the team level.

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Michael Naraine, Shannon Kerwin and Milena M. Parent

This case study explores the issue of team leadership among players who have been selected to play for their national team in an international tournament. After the coaching staff had solidified the roster, a total of 12 (fictional) players were chosen to represent Canada Basketball on the senior women’s development team. With some players having known their teammates for only 2 weeks, the coaching staff has asked the team’s analytics specialist to gather data regarding the network of players within the team and present potential captains of the team to the coaching staff. Students will take on the role of the analytics specialist and provide the summary of the analysis to the coaching staff. Specifically, using a social network analysis approach, students will use the team’s network of players to determine which individual players are involved in the team’s leadership structure as captains. The primary objective of this case study is to afford students an opportunity to be acquainted with social network analysis in a sport management setting.

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Marion E. Hambrick

Sport industry groups including athletes, teams, and leagues use Twitter to share information about and promote their products. The purpose of this study was to explore how sporting event organizers and influential Twitter users spread information through the online social network. The study examined two bicycle race organizers using Twitter to promote their events. Using social network analysis, the study categorized Twitter messages posted by the race organizers, identified their Twitter followers and shared relationships within Twitter, and mapped the spread of information through these relationships. The results revealed that the race organizers used their Twitter home pages and informational and promotional messages to attract followers. Popular Twitter users followed the race organizers early, typically within the first 4 days of each homepage’s creation, and they helped spread information to their respective followers. Sporting event organizers can leverage Twitter and influential users to share information about and promote their events.

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Sarah Edney, Tim Olds, Jillian Ryan, Ronald Plotnikoff, Corneel Vandelanotte, Rachel Curtis and Carol Maher

.1038/mp.2010.13 55. Simpkins SD , Shaefer DR , Price CD , Vest AE . Adolescent friendships, BMI, and physical activity: untangling selection and influence through longitudinal social network analysis . J Res Adolesc . 2013 ; 23 ( 3 ): 537 – 549 . doi:10.1111/j.1532-7795.2012.00836.x 10

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Howard L. Nixon II

The purpose of this paper is to focus more attention on the potential value of a structural social network approach for understanding social interaction, relationships, structures, and change in sport. Despite growing interest in this approach in sociology in general, little attention has been paid to it by sport sociologists. Examples of applications to sport are presented concerning the study of pain and injury, small groups and subcultures, organizational relations, coaching burnout and deviance, and managerial recruitment and stacking.

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Michael L. Naraine and Milena M. Parent

The purpose of this study was to examine national sport organizations’ (NSOs’) social networks on Twitter to explore followership between users, thereby illuminating powerful and central actors in a digital environment. Using a stratified, convenience sample, followership between the ego (i.e., NSO) and its alters (i.e., stakeholders) were noted in square, one-mode sociomatrices for the Fencing Canada (381 × 381) and Luge Canada (1026 × 1026) networks on Twitter. Using social network analysis to analyze the data for network density, average ties, Bonacich beta centrality, and core–periphery structure, the results indicate fans, elite athletes, photographers, competing sport organizations, and local clubs are some of the key stakeholders with large amounts of power. Though salient users, such as sponsors and international sport federations, are also present in the network core, NSOs seem better able to increase visibility of their content by targeting smaller scale users. The findings imply managers may wish to reflect upon how these advantaged users can be incorporated into their social communication strategies and how scholarship should continue examining followership as well as content in online settings.