Analysis of physical activity propagation in a health social network

CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management

Volumn , Issue , 2014, Pages 1329-1338

  Phan, NhatHai ^a   Dou, Dejing ^a   Xiao, Xiao ^a   Piniewski, Brigitte ^b   Kil, David ^c  

^a UNIVERSITY OF OREGON   (United States)

^b PeaceHealth Laboratories   (United States)

^c HealthMantic Inc ^*  (United States)

Author keywords

Health social network; Physical activity propagation

Indexed keywords

ECONOMIC AND SOCIAL EFFECTS; KNOWLEDGE MANAGEMENT;

DIFFERENT GRANULARITIES; EXPERIMENTAL EVALUATION; HIERARCHICAL APPROACH; INFLUENCE PATTERNS; PHYSICAL ACTIVITY; QUANTITATIVE STUDY; SOCIAL COMMUNICATIONS; SOCIAL INFLUENCE MODEL;

HEALTH;

EID: 84937598092     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2661829.2662025     Document Type: Conference Paper

References (29)

1. A. Bauman, T. Armstrong, J. Davies, N. Owen, W. Brown, B. Bellew, and P. Vita. Trends in physical activity participation and the impact of integrated campaigns among australian adults, 1997-99. Australian and New Zealand Journal of Public Health, 27(1):76-9, 2003.
2. N. Christakis and J. Fowler. The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357:370-9, 2007.
3. P. Domingos and M. Richardson. Mining the network value of customers. In Proceedings of KDD'01, pages 57-66, 2001.
4. A. Goyal, F. Bonchi, and L. V. S. Lakshmanan. Learning influence probabilities in social networks. In Proceedings of WSDM'10, pages 241-250, 2010.
5. http://www.internetworldstats.com/stats.htm.
6. G. Karypis and V. Kumar. A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J. Sci. Comput., 20(1):359-392, 1998.
7. D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network. In Proceedings of KDD'03, pages 137-146, 2003.
8. D. Kil, F. Shin, B. Piniewski, J. Hahn, and K. Chan. Impacts of social health data on predicting weight loss and engagement. In O'Reilly StrataRx Conference, San Francisco, CA, October 2012.
9. B. Marcus, C. Nigg, D. Riebe, and L. Forsyth. Interactive communication strategies: implications for population-based physical activity promotion. American Journal of Preventive Medicine, 19(2):121-6, 2000.
10. A. Marshall, E. Eakin, E. Leslie, and N. Owen. Exploring the feasibility and acceptability of using internet technology to promote physical activity within a defined community. Health promotion journal of Australia, 2005(16):82-4, 2005.
11. M. Mathioudakis, F. Bonchi, C. Castillo, A. Gionis, and A. Ukkonen. Sparsification of influence networks. In Proceedings of KDD'11, pages 529-537, 2011.
12. Y. Mehmood, N. Barbieri, F. Bonchi, and A. Ukkonen. Csi: Community-level social influence analysis. In Proceedings of ECML-PKDD'13, pages 48-63, 2013.
13. S. Navlakha, R. Rastogi, and N. Shrivastava. Graph summarization with bounded error. In Proceedings of SIGMOD'08, pages 419-432, 2008.
14. N. I. of Health. Aim for a healthy weight: Assess you risk. National Institutes of Health, 2007.
15. U. D. of Health and H. Services. Physical activity an health: A report of the surgeon general. Atlanta GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Nationa Center for Chronic Disease Prevention and Health Promotion, 1996.
16. R. Pate, M. Pratt, S. Blair, and et al. Physical activit and public health. a recommendation from the center for disease control and prevention and the american college of sports medicine. JAMA, 273(5):402-7, 1995
17. K. Patrick. Information technology and the future of preventive medicine: potential, pitfalls, and policy. American Journal of Preventive Medicine, 19(2):132-5, 2000.
18. J. Prochaska, M. Zabinski, K. Calfas, J. Sallis, and K. Patrick. Pace+: interactive communication technology for behavior change in clinical settings. American Journal of Preventive Medicine, 19(2):127-31, 2000.
19. J. Rissanen. A universal prior for integers and estimation by minimum description length. The annals of statistics, 14(5):416-431, 1983.
20. L. Ritterband, L. Gonder-Frederick, D. Cox, A. Clifton, R. West, and S. Borowitz. Internet interventions: in review, in use, and into the future. Professional Psychology: Research and Practice, 34:527-34, 2003.
21. K. Saito, R. Nakano, and M. Kimura. Prediction of information diffusion probabilities for independent cascade model. In Proceedings of KES 2008, pages 67-75, 2008.
22. G. Schwarz. Estimating the dimension of a model. Th annals of statistics, 6(2):461-464, 1978.
23. Y. Shen, R. Jin, D. Dou, N. Chowdhury, J. Sun, B. Piniewski, and D. Kil. Socialized gaussian process model for human behavior prediction in a health social network. In ICDM'12, pages 1110-1115, 2012.
24. J. Tang, J. Sun, C. Wang, and Z. Yang. Social influence analysis in large-scale networks. In Proceedings of KDD'09, pages 807-816, 2009.
25. R. Taylor. Use of body mass index for monitoring growth and obesity. Paediatrics & Child Health, 15(5):258, 2010.
26. Y. Tian, R. Hankins, and J. Patel. Efficient aggregation for graph summarization. In Proceedings of SIGMOD'08, pages 567-580, 2008.
27. C. Vandelanotte, K. Spathonis, E. Eakin, and N. Owen. Website-delivered physical activity interventions: A review of the literature. American Journal of Preventive Medicine, 33(1):54-64, 2007.
28. R. Xiang, J. Neville, and M. Rogati. Modeling relationship strength in online social networks. In Proceedings of WWW'10, pages 981-990, 2010.
29. N. Zhang, Y. Tian, and J. Patel. Discovery-driven graph summarization. In Proceedings of ICDE'10, pages 880-891, 2010.