Big social data analytics for public health: Facebook engagement and performance

2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016

Volumn , Issue , 2016, Pages

  Straton, Nadiya ^a   Hansen, Kjeld ^a,b,c   Mukkamala, Raghava Rao ^a   Hussain, Abid ^a   Grønli, Tor Morten ^b   Langberg, Henning ^c   Vatrapu, Ravi ^a,b  

^a Copenhagen Business School ^*  (Denmark)

^b WESTERDALS OSLO SCHOOL OF ARTS   (Norway)

^c UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; HEALTH; LEARNING SYSTEMS; SOCIAL NETWORKING (ONLINE);

CLUSTERING RESULTS; FACEBOOK; HEALTH INFORMATIONS; PUBLIC ORGANISATION; SOCIAL DATUM; SOCIAL MEDIA; UNSUPERVISED MACHINE LEARNING; USER ENGAGEMENT;

PUBLIC HEALTH;

EID: 85006380060     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HealthCom.2016.7749497     Document Type: Conference Paper

References (15)

1. M. P. Hamm, A. Chisholm, J. Shulhan, A. Milne, S. D. Scott, T. P. Klassen, and L. Hartling, "Social media use by health care professionals and trainees: a scoping review," Academic Medicine, vol. 88, no. 9, pp. 1376-1383, 2013.
2. R. Vatrapu, "Understanding social business." in Emerging Dimensions of Technology Management. Springer, 2013, pp. 147-158.
3. J. Ashton and H. Seymour, The New Public Health: The Liverpool Experience. Buckingham: Open University Press, 1992.
4. A. Petersen and D. Lupton, The new public health: Health and self in the age of risk. Sage Publications, Inc, 1996.
5. P. A. Bath, "Health informatics: current issues and challenges," Journal of Information Science, 2008.
6. N. A. Christakis and J. H. Fowler, Connected: The surprising power of our social networks and how they shape our lives. Little, Brown, 2009.
7. K. Kunst and R. Vatrapu, "Towards a theory of socially shared consumption: Literature review, taxonomy and research agenda," in Proceedings of the European Conference on Information Systems (ECIS), Tel Aviv, Israel, 2014.
8. P. Balatsoukas, C. M. Kennedy, I. Buchan, J. Powell, and J. Ainsworth, "The role of social network technologies in online health promotion: A narrative review of theoretical and empirical factors influencing intervention effectiveness," Journal of medical Internet research, vol. 17, no. 6, 2015.
9. C. Hawn, "Take two aspirin and tweet me in the morning: how twitter, facebook, and other social media are reshaping health care," Health affairs, vol. 28, no. 2, pp. 361-368, 2009.
10. M. Burke and M. Develin, "Once more with feeling: Supportive responses to social sharing on facebook," in Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. ACM, 2016, pp. 1462-1474.
11. A. Hussain, R. Vatrapu, D. Hardt, and Z. Jaffari, "Social data analytics tool: A demonstrative case study of methodology and software." in Analysing Social Media Data and Web Networks, M. C. Rachel Gibson and S. Ward, Eds. Palgrave Macmillan, 2014 (in press).
12. A. K. Jain, "Data clustering: 50 years beyond k-means," Pattern recognition letters, vol. 31, no. 8, pp. 651-666, 2010.
13. P. Berkhin, "A survey of clustering data mining techniques," in Grouping multidimensional data. Springer, 2006, pp. 25-71.
14. J. A. Hartigan and M. A. Wong, "Algorithm as 136: A k-means clustering algorithm," Journal of the Royal Statistical Society. Series C (Applied Statistics), vol. 28, no. 1, pp. 100-108, 1979.
15. R. Tibshirani, G. Walther, and T. Hastie, "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 63, no. 2, pp. 411-423, 2001.