Skip to main content

Collaborative Friendship Networks in Online Healthcare Communities: An Exponential Random Graph Model Analysis

  • Conference paper
Smart Health (ICSH 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8549))

Included in the following conference series:

Abstract

Health 2.0 provides patients an unprecedented way to connect with each other online. However, less attention has been paid to how patient collaborative friendships form in online healthcare communities. This study examines the relationship between collaborative friendship formation and patients’ characteristics. Results from Exponential Random Graph Model (ERGM) analysis indicate that gender homophily doesn’t appear in CFNs, while health homophily such as treatments homophily and health-status homophily increases the likelihood of collaborative friendship formation. This study provides insights for improving website design to help foster close relationship among patients and deepen levels of engagement.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: Homophily in social networks. Annual Review of Sociology, 415–444 (2001)

    Google Scholar 

  2. Ibarra, H.: Homophily and differential returns: Sex differences in network structure and access in an advertising firm. Administrative Science Quarterly 37, 422–447 (1992)

    Article  MathSciNet  Google Scholar 

  3. Mollica, K.A., Gray, B., Trevino, L.K.: Racial homophily and its persistence in newcomers’ social networks. Organization Science 14, 123–136 (2003)

    Article  Google Scholar 

  4. Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: From big data to big impact. MIS Quarterly 36, 1165–1188 (2012)

    Google Scholar 

  5. Monge, P.R., Contractor, N.S.: Theories of communication networks. Oxford University Press, New York (2003)

    Google Scholar 

  6. Stewart, S.A., Abidi, S.S.R.: Applying Social Network Analysis to Understand the Knowledge Sharing Behaviour of Practitioners in a Clinical Online Discussion Forum. Journal of medical Internet research 14, e170 (2012)

    Google Scholar 

  7. Granovetter, M.S.: The strength of weak ties. American Journal of Sociology, 1360–1380 (1973)

    Google Scholar 

  8. Centola, D.: The spread of behavior in an online social network experiment. Science 329, 1194–1197 (2010)

    Article  Google Scholar 

  9. Centola, D.: An experimental study of homophily in the adoption of health behavior. Science 334, 1269–1272 (2011)

    Article  Google Scholar 

  10. Chang, H.J.: Online supportive interactions: using a network approach to examine communication patterns within a psychosis social support group in Taiwan. Journal of the American Society for Information Science and Technology 60, 1504–1517 (2009)

    Article  Google Scholar 

  11. Durant, K.T., McCray, A.T., Safran, C.: Social network analysis of an online melanoma discussion group. In: AMIA Summits on Translational Science Proceedings (2010)

    Google Scholar 

  12. Chomutare, T., Årsand, E., Hartvigsen, G.: Characterizing development patterns of health-care social networks. Network Modeling Analysis in Health Informatics and Bioinformatics, 1–11 (2013)

    Google Scholar 

  13. Chuang, K.Y., Yang, C.C.: How do e-patients connect online? a study of social support roles in health social networking. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds.) SBP 2013. LNCS, vol. 7812, pp. 193–200. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  14. Durant, K.T., McCray, A.T., Safran, C.: Identifying gender-Preferred communication styles within online cancer communities: A retrospective, longitudinal Analysis. PloS One 7, e49169 (2012)

    Google Scholar 

  15. Yan, L., Tan, Y., Peng, J.: Network dynamics: How can we find patients likeus? Available at SSRN (2011), http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1820748

  16. Wasserman, S., Pattison, P.: Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp. Psychometrika 61, 401–425 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  17. Robins, G.: Exponential random graph models for social networks. In: Handbook of Social Network Analysis. Sage (2011)

    Google Scholar 

  18. Handcock, M.S., Hunter, D.R., Butts, C.T., Goodreau, S.M., Morris, M.: Statnet: Software tools for the representation, visualization, analysis and simulation of network data. Journal of Statistical Software 24, 1548 (2008)

    Google Scholar 

  19. Wardle, J., Haase, A.M., Steptoe, A., Nillapun, M., Jonwutiwes, K., Bellisie, F.: Gender differences in food choice: the contribution of health beliefs and dieting. Annals of Behavioral Medicine 27, 107–116 (2004)

    Article  Google Scholar 

  20. Sugawara, Y., Narimatsu, H., Hozawa, A., Shao, L., Otani, K., Fukao, A.: Cancer patients on Twitter: a novel patient community on social media. BMC Research Notes 5, 699 (2012)

    Article  Google Scholar 

  21. Charnock, D., Shepperd, S., Needham, G., Gann, R.: DISCERN: an instrument for judging the quality of written consumer health information on treatment choices. Journal of Epidemiology and Community Health 53, 105–111 (1999)

    Article  Google Scholar 

  22. De La Haye, K., Robins, G., Mohr, P., Wilson, C.: Homophily and contagion as explanations for weight similarities among adolescent friends. Journal of Adolescent Health 49, 421–427 (2011)

    Article  Google Scholar 

  23. Byrne, D.: Attitudes and attraction. Advances in Experimental Social Psychology 4, 35–89 (1969)

    Article  MathSciNet  Google Scholar 

  24. Huston, T.L., Levinger, G.: Interpersonal attraction and relationships. Annual Review of Psychology 29, 115–156 (1978)

    Article  Google Scholar 

  25. Mehra, A., Kilduff, M., Brass, D.J.: At the margins: A distinctiveness approach to the social identity and social networks of underrepresented groups. Academy of Management Journal 41, 441–452 (1998)

    Article  Google Scholar 

  26. Shrum, W., Cheek Jr., N.H., MacD, S.: Friendship in school: Gender and racial homophily. Sociology of Education, 227–239 (1988)

    Google Scholar 

  27. Smith, K.P., Christakis, N.A.: Social networks and health. Annual Review of Sociology 34, 405–429 (2008)

    Article  Google Scholar 

  28. Diaz, J.A., Griffith, R.A., Ng, J.J., Reinert, S.E., Friedmann, P.D., Moulton, A.W.: Patients’ use of the Internet for medical information. Journal of General Internal Medicine 17, 180–185 (2002)

    Article  Google Scholar 

  29. Shuyler, K.S., Knight, K.M.: What are patients seeking when they turn to the Internet? Qualitative content analysis of questions asked by visitors to an orthopaedics Web site. Journal of Medical Internet Research 5 (2003)

    Google Scholar 

  30. Pereira, J.L., Koski, S., Hanson, J., Bruera, E.D., Mackey, J.R.: Internet usage among women with breast cancer: an exploratory study. Clinical Breast Cancer 1, 148–153 (2000)

    Article  Google Scholar 

  31. Knowler, W.C., Barrett-Connor, E., Fowler, S.E., Hamman, R.F., Lachin, J.M., Walker, E.A., Nathan, D.M.: Reduction in the incidence of type II diabetes with lifestyle intervention or metformin. New England Journal of Medicine 346, 393–403 (2002)

    Article  Google Scholar 

  32. Guo, S.E., Huang, C.Y., Hsu, H.T.: Information needs among patients with chronic obstructive pulmonary disease at their first hospital admission: priorities and correlates. Journal of Clinical Nursing (2013)

    Google Scholar 

  33. Festinger, L.: A theory of social comparison processes. Human Relations 7, 117–140 (1954)

    Article  Google Scholar 

  34. Helgeson, V.S., Taylor, S.E.: Social comparisons and adjustment among cardiac patients1. Journal of Applied Social Psychology 23, 1171–1195 (1993)

    Article  Google Scholar 

  35. Wood, J.V., VanderZee, K.: Social comparisons among cancer patients: under what conditions are comparisons upward and downward? In: Health, Coping, and Well-being, pp. 299–328 (1997)

    Google Scholar 

  36. Harris, D.M., Guten, S.: Health-protective behavior: An exploratory study. Journal of Health and Social Behavior, 17–29 (1979)

    Google Scholar 

  37. King, R.A., Rotter, J.I., Motulsky, A.G.: The genetic basis of common diseases. Oxford University Press (2002)

    Google Scholar 

  38. Gordon, P., West, J., Jones, H., Gibson, T.: A 10 year prospective followup of patients with rheumatoid arthritis 1986-96. The Journal of Rheumatology 28, 2409–2415 (2001)

    Google Scholar 

  39. Van Gaalen, F.A., Toes, R.E., Ditzel, H.J., Schaller, M., Breedveld, F.C., Verweij, C.L., Huizinga, T.W.: Association of autoantibodies to glucose-6-phosphate isomerase with extraarticular complications in rheumatoid arthritis. Arthritis & Rheumatism 50, 395–399 (2004)

    Article  Google Scholar 

  40. Thelwall, M.: Homophily in myspace. Journal of the American Society for Information Science and Technology 60, 219–231 (2008)

    Article  Google Scholar 

  41. Ma, X., Chen, G., Xiao, J.: Analysis of an online health social network. Paper presented at the Proceedings of the 1st ACM International Health Informatics Symposium (2010)

    Google Scholar 

  42. Van De Belt, T.H., Engelen, L.J., Berben, S.A., Schoonhoven, L.: Definition of Health 2.0 and Medicine 2.0: a systematic review. Journal of Medical Internet Research 12, e18 (2010)

    Google Scholar 

  43. Pahor, M., Škerlavaj, M., Dimovski, V.: Evidence for the network perspective on organizational learning. Journal of the American Society for Information Science and Technology 59, 1985–1994 (2008)

    Article  Google Scholar 

  44. Su, C., Contractor, N.: A multidimensional network approach to studying team members’ information seeking from human and digital knowledge sources in consulting firms. Journal of the American Society for Information Science and Technology 62, 1257–1275 (2011)

    Article  Google Scholar 

  45. Snijders, T.A.B.: Markov chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure 3, 1–40 (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Song, X., Jiang, S., Yan, X., Chen, H. (2014). Collaborative Friendship Networks in Online Healthcare Communities: An Exponential Random Graph Model Analysis. In: Zheng, X., Zeng, D., Chen, H., Zhang, Y., Xing, C., Neill, D.B. (eds) Smart Health. ICSH 2014. Lecture Notes in Computer Science, vol 8549. Springer, Cham. https://doi.org/10.1007/978-3-319-08416-9_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08416-9_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08415-2

  • Online ISBN: 978-3-319-08416-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics