Abstract
The influence of social connections on human behaviour has been demonstrated in many occasions. This paper presents the analysis of the dynamic properties of longitudinal (335 days) community data (n=3,375 participants) from an online health promotion program. The community data is unique as it describes how the network has evolved since its inception and because the information exchanged through the network was predominantly about the achievements of participants in the program and therefore influencing behavior through social comparison. The analyses show that the largest component of the community network has characteristics of a small world network. The analyses also show that connections are formed according to a strong attachment preference according to the gender, and a weaker homophily for Body Mass Index. The presented analysis can serve as basis for creating novel interventions that influence physical activity behavior through social connections.
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Keywords
- Social Network
- Social Network Analysis
- Large Component
- Betweenness Centrality
- Physical Activity Behavior
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Acemoglu, D., Ozdaglar, A.: Opinion dynamics and learning in social networks. Dynamic Games and Applications 1(1), 3–49 (2011)
Acemoglu, D., Ozdaglar, A., ParandehGheibi, A.: Spread of (mis) information in social networks. Games and Economic Behavior 70, 194–227 (2010)
Araújo, E.F.M., Tran, A.V.T.T., Mollee, J.S., Klein, M.C.A.: Analysis and evaluation of social contagion of physical activity in a group of young adults. In: ACM International Conference Proceeding Series, vol. 07-09-Ocob (2015)
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(October), 509–512 (1999)
Blankendaal, R., Parinussa, S., Treur, J.: A temporal-causal modelling approach to integrated contagion and network change in social networks. In: Proceedings of the 22nd European Conference on Artificial Intelligence, ECAI16 (2016)
Christakis, N.a., Fowler, J.H.: The spread of obesity in a large social network over 32 years. The New England journal of medicine 357(4), 370–9 (2007)
Duck, S., Wright, P.H.: Reexamining gender differences in same-gender friendships: A close look at two kinds of data. Sex Roles 28(11-12), 709–727 (1993)
Ellison, N.B., Steinfield, C., Lampe, C.: The benefits of facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication 12(4), 1143–1168 (2007)
Eubank, S., Guclu, H., Kumar, V.S., Marathe, M.V., Srinivasan, A., Toroczkai, Z., Wang, N.: Modelling disease outbreaks in realistic urban social networks. Nature 429(6988), 180–184 (2004)
Groenewegen, M., Stoyanov, D., Deichmann, D., van Halteren, A.: Connecting with active people matters: the influence of an online community on physical activity behavior. In: International Conference on Social Informatics, pp. 96–109. Springer (2012)
Kempe, D., Kleinberg, J., Tardos, É.: Influential Nodes in a Diffusion Model for Social Networks. Automata, Languages and Programming 3580, 1127–1138 (2005)
Lazarsfeld, P.F., Merton, R.K.: Friendship as a Social Process: A Substantive and Methodological analysis. Freedom and Control in Modern Society 18, 18–66 (1954)
Manzoor, A., Mollee, J.S., Araújo, E.F., van Halteren, A.T., Klein, M.C.A.: Online sharing of physical activity: does it accelerate the impact of a health promotion program? In: Socialcom 2016 (2016)
Mcpherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology 27(1), 415–444 (2001)
Mislove, A., Marcon, M., Gummadi, K.P., Druschel, P., Bhattacharjee, B.: Measurement and analysis of online social networks. Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement - IMC ’07 pp. 29–42 (2007)
Newman, M.E.J.: The structure and function of complex networks. Siam Review 45(2), 167–256 (2003)
Newman, M.E.J., Watts, D.J.: Scaling and percolation in the small-world network model. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics 60(6 Pt B), 7332–7342 (1999)
Organization, W.H., et al.: Global database on body mass index: an interactive surveillance tool for monitoring nutrition transition. World Health Organization: Geneva (2012)
Scott, J.: Social Network Analysis. Sage (2012)
Tsvetovat, M., Kouznetsov, A.: Social Network Analysis for Startups: Finding connections on the social web. “O’Reilly Media, Inc.” (2011)
Valente, T.W.: Network models of the diffusion of innovations, vol. 2. Hampton Press (NJ) (1995)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440–2 (1998)
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de Mello Araújo, E.F., Klein, M., van Halteren, A. (2017). Social Connection Dynamics in a Health Promotion Network. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016. Studies in Computational Intelligence, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-50901-3_61
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DOI: https://doi.org/10.1007/978-3-319-50901-3_61
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