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Diogo Peixoto, Gibson Moreira Praça, Sarah Bredt and Filipe Manuel Clemente

Networks. 2012;34(4):682-690; doi: 10.1016/j.socnet. 2012.08.004. 7. Clemente FM, Martins FML, Mendes RS. Social network analysis applied to team sports analysis. Cham: Springer International Publishing; 2016. 8. Peña JL, Touchette H. A network theory analysis of football strategies. In: Clanet C (ed.), Sports physics: proceedings of 2012 Euromech physics of sports conference. Palaiseau: Éditions de l’École polytechnique; 2012; 517-528. 9. Clemente FM, Martins FML, Wong DP, Kalamaras D, Mendes RS. Midfielder as the

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Patrizia Zagnoli and Elena Radicchi

. Corriere della Sera , 1 Marzo. Benassai, D. (1998). Firenze: un amore viola. Firenze: Edizioni Scramasax. Burt, R. S. (1982). Toward a Structural Theory of Social Action. New York: Academic Press. Burt, R. S. (1983). Range. In R. S. Burt, M. J. Minor (Ed.), Applied Network Analysis. A Methodological Introduction. Beverly Hills: Sage. Coppini, A. (2009). L'informazione e l'eccesso di comunicazione: ostacoli immateriali e fisici alla realizzazione dello stadio

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Tamás Dóczi

Active Sport Tourism in the Hungarian Population: Current Trends and Perspectives

In the past few decades, sport and tourism, two significant industries, have gone through a phase of rapid development. The relationship between the two fields is becoming more and more recognized by economic actors, policymakers and social scientists as well; nevertheless, there is a question of how widespread active sport tourism is in the different social groups of Hungarian society, and what the perspectives of sport tourism are as a leisure time activity in the future. The objective of the current paper is to answer these questions, based on survey research conducted in a representative sample (n=1027) of the Hungarian adult population. In the first phase of data analysis, the author focused on the following two questions: (1) What percentage of the population is engaged in doing regular physical exercise, and travelling during their holidays? (2) Is there a relationship between doing exercise and travelling? Based on the two dimensions (physical exercise and travelling) four groups could be separated, the in-depth analysis of the groups was carried out in the second phase of the data analysis. During this phase, the following questions were in focus: (1) How can the four groups be characterized concerning their socio-economic status? (2) What leisure activities are characteristic of them? (3) What can be said about the social networks of the members of these groups? (4) How can we characterize their attitudes to healthy lifestyle, and within this, sport? According to the results, the social basis of active sport tourism is not very wide. The majority of the Hungarian population is hindered by worsening living standards and worsening health levels, and by the lack of adequate knowledge about active sport tourism and the positive impact of it on the quality of life. A further problem is that although many people are familiar with the influence of lifestyle on health, and recognize the benefits of exercise in theory, in reality few people are involved in sporting activities, and for many, doing exercise is not a source of pleasure. That is why it is important that the messages referring to the positive impact of regular physical exercise reach the different social groups. In these messages, besides the often stressed health-preserving role, social and recreational aspects of sport as a leisure time activity should also be emphasized.

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F. M. Clemente and F. M. L. Martins

soccer teams in FIFA World Cup 2014. International Journal of Performance Analysis in Sport , 15 (1), 80–96. Clemente, F. M., Martins, F. M. L., & Mendes, R. S. (2016). Social Network Analysis Applied to Team Sports Analysis . Netherlands: Springer International Publishing. Duarte, R., Araújo, D., Correia, V., & Davids, K. (2012). Sports Teams as Superorganisms: Implications of Sociobiological Models of Behaviour for Research and Practice in Team Sports Performance Analysis. Sports Medicine , 42 (8), 633

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Chew Swee Seng and Leng Ho Keat

-230. Burnkrant, R.E., & Cousineau, A. (1975). Informational and normative social influence in buyer behavior. Journal of Consumer Research, 206-215. Cha, J. (2009). Shopping on social networking Web sites: Attitudes toward real versus virtual items. Journal of Interactive Advertising, 10(1), 77-93. Cohen, J. (1988). Statistical power analysis for the behavioral sciences: Lawrence Erlbaum. Coyle, J.R., & Thorson, E. (2001). The effects of progressive levels of interactivity and vividness in web marketing sites. Journal of

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Filipe Manuel Clemente, Micael Santos Couceiro, Fernando Manuel Lourenço Martins and Rui Sousa Mendes

Angeles, CA; 2005 Malta P, Travassos B. Characterization of the defense-attack transition of a soccer team. Motricidade, 2014; 10: 27-37 Memmert D, Perl J. Game creativity analysis using neural networks. J Sport Sci, 2009; 27: 139-149 Passos P, Davids K, Araújo D, Paz N, Minguéns J, Mendes J. Networks as a novel tool for studying team ball sports as complex social systems. J Sci Med Sport, 2011; 14: 170-176 Peña JL, Touchette H. A network theory analysis of football strategies. In Clanet C (Ed.), Sports

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Sun J. Kang, Jason A. Rice, Marion E. Hambrick and Chulhwan Choi

. Communication & Sport. DOI: 10.1177/2167479513518044. Hambrick, M.E., & Mahoney, T.Q. (2011). “It’s incredible - trust me”: Exploring the role of celebrity athletes as marketers in online social networks. International Journal of Sport Management and Marketing, 10, 161-179. DOI: 10.1504/IJSMM.2011.044794. Lombard, M., Snyder-Duch, J., & Bracken, C.C. (2002). Content analysis in mass communication: Assessment and reporting of intercoder reliability. Human Communication Research, 28, 587-604. DOI: 10.1111/j.1468-2958.2002.tb00826.x. Mahoney, T

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Bruno Mendes, Filipe Manuel Clemente and Nuno Maurício

(match location, match status or quality of opposition) ( Taylor et al., 2008 ). Despite the importance of such variables, current mathematical techniques have been employed to improve the ability to identify collective properties that are not analyzed in the classical notational process ( Bloomfield et al., 2005 ; Duch et al., 2010 ). One of these techniques is social network analysis (SNA) ( Wasserman and Faust, 1994 ). SNA uses graph theory to identify the relationships between members of an organization or team ( Lusher et al., 2010 ). The general properties of

Open access

Tomáš Gajdošík

References Baggio, R. (2008). Network Analysis of a Tourism Destination (Doctoral dissertation). Queensland: University of Queensland. Retrieved from Baggio, R., Scott, N., & Cooper, C. (2010). Network Science. A Review focused on Tourism. Annals of Tourism Research, 37(3), 802 - 827. Beritelli, P. (2011). Tourist Destination governance through local elites - Looking beyond the stakeholder level (Cumulative Postdoctoral Thesis). St. Gallen: University of St

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Anna Staszewska and Michał Żemła

. Journal of Travel Research, 46(1), 96-107. Bornhorst, T., Ritchie, J. R. B., & Sheehan, L. (2010). Determinants of tourism success for DMOs & destinations: An empirical examination of stakeholders’ perspectives. Tourism Management , 31(5), 572-589. Chung, K. K., Hossain, L., & Davis, J. (2005, November). Exploring sociocentric and egocentric approaches for social network analysis. In Proceedings of the 2nd international conference on knowledge management in Asia Pacific. Buhalis, D. (2000). Marketing the competitive