2,004
Views
97
CrossRef citations to date
0
Altmetric
ARTICLES

Cancer Talk on Twitter: Community Structure and Information Sources in Breast and Prostate Cancer Social Networks

&
Pages 210-225 | Published online: 10 Oct 2013
 

Abstract

This study suggests taking a social networks theoretical approach to predict and explain patterns of information exchange among Twitter prostate and breast cancer communities. The authors collected profiles and following relationship data about users who posted messages about either cancer over 1 composite week. Using social network analysis, the authors identified the main clusters of interconnected users and their most followed hubs (i.e., information sources sought). Findings suggest that users who populated the persistent-across-time core cancer communities created dense clusters, an indication of taking advantage of the technology to form relationships with one another in ways that traditional one-to-many communication technologies cannot support. The major information sources sought were very specific to the community health interest and were grassroots oriented (e.g., a blog about prostate cancer treatments). Accounts associated with health organizations and news media, despite their focus on health, did not play a role in these core health communities. Methodological and practical implications for researchers and health campaigners are discussed.

Notes

*Number of following relationships among users in the network.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 215.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.