- Title
- Mapping the anti-vaccination movement on Facebook
- Creator
- Smith, Naomi; Graham, Tim
- Date
- 2019
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/170417
- Identifier
- vital:14180
- Identifier
-
https://doi.org/10.1080/1369118X.2017.1418406
- Identifier
- ISBN:1369-118X
- Abstract
- Over the past decade, anti-vaccination rhetoric has become part of the mainstream discourse regarding the public health practice of childhood vaccination. These utilise social media to foster online spaces that strengthen and popularise anti-vaccination discourses. In this paper, we examine the characteristics of and the discourses present within six popular anti-vaccination Facebook pages. We examine these large-scale datasets using a range of methods, including social network analysis, gender prediction using historical census data, and generative statistical models for topic analysis (Latent Dirichletallocation). We find that present-day discourses centre around moral outrage and structural oppression by institutional government and the media, suggesting a strong logic of 'conspiracy-style' beliefs and thinking. Furthermore, anti-vaccination pages on Facebook reflect a highly 'feminised' movement the vast majority of participants are women. Although anti-vaccination networks on Facebook are large and global in scope, the comment activity sub-networks appear to be 'small world'. This suggests that social media may have a role in spreading anti-vaccination ideas and making the movement durable on a global scale.
- Publisher
- Routledge; imprint of Taylor & Francis
- Relation
- Information Communication & Society Vol. 22, no. 9 (2019), p. 1310-1327
- Rights
- Copyright © 2017 Informa UK Limited, trading as Taylor & Francis Group
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0806 Information Systems; 0807 Library and Information Studies; 2001 Communication and Media Studies; Anti-vaccination; Social network analysis; Topic modelling; Social network sites; Social media
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