Collaborative friendship networks in online healthcare communities: An exponential random graph model analysis

Xiaolong Song, Shan Jiang, Xianbin Yan, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationSmart Health - International Conference, ICSH 2014, Proceedings
PublisherSpringer-Verlag
Pages75-87
Number of pages13
ISBN (Print)9783319084152
DOIs
StatePublished - Jan 1 2014
Event2nd International Conference for Smart Health, CSH 2014 - Beijing, China
Duration: Jul 10 2014Jul 11 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8549 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference for Smart Health, CSH 2014
CountryChina
CityBeijing
Period7/10/147/11/14

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Keywords

  • Collaborative friendship
  • ERGMs
  • Health 2.0
  • Patient networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Song, X., Jiang, S., Yan, X., & Chen, H. (2014). Collaborative friendship networks in online healthcare communities: An exponential random graph model analysis. In Smart Health - International Conference, ICSH 2014, Proceedings (pp. 75-87). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8549 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-08416-9_8