CIS607, Spring 2012

Social Networks and Health Informatics

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• Course Description:

  Social Network Analysis and Health Informatics are two active research areas both related to several computer science disciplines, such as Databases, Web, Network, Data Mining, and Machine Learning, as well as applications in industry. Social networks are social structures composed of individuals (or organizations) which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest etc. Social network analysis (SNA) is the measuring, mapping, analyzing, and interpretation of social network structures, the connections between individuals (or organizations). Health care is an important issue to every individual and organization in the current society. Health informatics deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of information in health and biomedicine. Several recent scientific studies have found that real-life social networks are quite relevant to health. For example, previous studies suggest that social networks have an obvious effect on spreading bad health behaviors, such as overweight, obesity, depression, and alcohol. Sometime the effect is even greater than person's genetics. However, previous studies also show that good health behaviors are hard to spread in the social networks. On the other hand, there are some critiques on statistical analysis on social network influence in health outcomes.
  
  This graduate research seminar will cover the following topics: the survey of basic concepts of social network analysis and health informatics, the influence of social networks to health outcomes, the strategies that operate on social networks to improve human health. The focus of this seminar is not to design a new social network but to understand the science of SNA in ways that will enhance its utility for improving human health. The instructor will give some introduction about those topics in a couple of lectures. Students are expected to read and discuss papers from journals or conference proceedings or from unpublished manuscripts on the Web. Each student is expected to give one or two presentations about the paper(s) or the topic he/she is interested in. The final report for each student can be a survey paper or a small implementation.

• Prerequisites:

  None. Basic knowledge of Databases, Web, statistics, data mining, and machine learning will be helpful.

• Time and Place:

  Fridays 2:00-3:20, 260 Deschutes Hall.

• Instructor:

  Dejing Dou, 303 Deschutes, phone 346-4572, email dou@cs.uoregon.edu.

• Office hours:

  Fridays 3:30-5:00 or by appointment.

• Evaluation:

  There is no exam for this seminar. Attendance and participation, paper reading, paper presentation and final report will determine the course score. Students will be encouraged to conduct further research projects from the topics discussed in this seminar, but it is not the requirement. Some more detail.

• Schedule and Lecture Notes:

  • Week 1 (Apr 6): course info, general introduction
  • Week 2 (Apr 13): introduction to each topic
  • Week 3 (Apr 20): Hao Wang's presentation
  • Week 4 (Apr 27): Yang Shu's presentation
  • Week 5 (May 4): Xiao Yuan's presentation
  • Week 6 (May 11): Srishti Nautiyal's presentation
  • Week 7 (May 18): Shangpu Jiang's presentation
  • Week 8 (May 25): Paul Elliott's presentation
  • Week 9 (Jun 1): Nafisa Afin Chowdhury's presentation
  • Final week (Jun 15): Fernando Gutierrez's presentation

• Homework:

• Papers for Reading (keeping updated):

  • Surveys on Social Network Analysis and Health Informatics
  • D. Lazer, A. Pentland, L. Adamic, et al, and M. Alstyne Computational Social Science. Science VOL 323, Issue 5915, pp. 721-723, 2009.
  • LC Freeman The development of social network analysis. Empirical Press 2004.
  • L. Getoor and C. Diehl Link mining: a survey. SIGKDD Explor. Newsl. 7(2), pp. 3-12, 2005.
  • A. Anagnostopoulos, R. Kumar, and M. Mahdian. Influence and correlation in social networks. In Proceedings of KDD, pp. 7-15, 2008.
  • A. Friede, H. Blum, and M. McDonald. Public Health Informatics: How Information-Age Technology Can Strengthen Public Health. Annual Review of Public Health. 16, pp. 239-252, 2005.
  • Peter A. Bath. Health informatics: current issues and challenges. Journal of Information Science, 34(4), pp. 501-518, 2008
  • B. Piniewski, J. Muskens, L. Estevez, R. Carroll, and R. Cnossen. Empowering healthcare patients with smart technology. IEEE Computer, 43(7), pp. 27-34, 2010.
  • S. Arala, L. Muchnika, and A. Sundararajana. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. PNAS, vol. 106,
    no. 51, pp. 21544-21549, 2009.
  • Influence of Social Networks to Health Care
  • N. Christakis and J. Fowler. The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357(4), pp. 370-379, 2007.
  • J. G. Trogdon, J. Nonnemakera, and J. Pais. Peer effects in adolescent overweight. Journal of Health Economics, 27(5), pp. 1388-1399, 2008.
  • N. Christakis and J. Fowler. The collective dynamics of smoking in a large social network. New England Journal of Medicine, 358 (21), pp. 2249-2258, 2008.
  • J. Rosenquist, J. Fowler, and N. Christakis. Social network determinants of depression. Molecular Psychiatry, pages 1-9, 2010.
  • J. Rosenquist, J. Murabito, J. Fowler, and N. Christakis. The spread of alcohol consumption behavior in a large social network. Annals of Internal Medicine, 152(7), pp. 426-433, 2010.
  • Use of Social Networks for Improving Human Health
  • R.R. Wing, and R.W. Jeffery. Benefits of Recruiting Participants With Friends and Increasing Social Support for Weight Loss and Maintenance. Journal of Consulting and Clinical Psychology Vol. 67, No. I, pp. 132-138, 1999.
  • C.S. Malchodi, C. Oncken, E.A. Dornelas, L. Caramanica, E. Gregonis, and S.L. Curry The Effects of Peer Counseling on Smoking Cessation and Reduction. Obstetricians and Gynecologists VOL. 101, NO. 3, pp. 504-510, 2003.
  • A. Barabasi Network medicine - from obesity to the "diseasome". New England Journal of Medicine, 357(4), pp. 404-407, 2007.
  • N. Mulvaney-Day and C. A.Womack. Obesity, identity and community: Leveraging social networks for behavior change in public health. Public Health Ethics, 2(3), pp. 250-260, 2009.
  • G. G. Bennett and R. E. Glasgow. The delivery of public health interventions via the internet: actualizing their potential. Annual Review of Public Health, 30, pp. 273-292, 2009.
  • Critiques
  • R. Lyons The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis. Statistics, Politics, and Policy Vol. 2, Issue 1, Article 2, 2011
  • C. R. Shalizi and A. C. Thomas Homophily and Contagion Are Generically Confounded in Observational Social Network Studies. Sociological Methods & Research 40(2) pp. 211-239, 2011

• Useful Links

  • Social Network Analysis
  • International Network for Social Network Analysis
  • The Biomedical Informatics Research Network