Tracking the Structure and Sentiment of Vaccination Discussions on
Mumsnet
- URL: http://arxiv.org/abs/2308.13014v1
- Date: Thu, 24 Aug 2023 18:28:35 GMT
- Title: Tracking the Structure and Sentiment of Vaccination Discussions on
Mumsnet
- Authors: Miguel E. P. Silva, Rigina Skeva, Thomas House, Caroline Jay
- Abstract summary: Vaccination is one of the top 10 threats to global health in 2019 by the World Health Organization.
Online social media has been identified as a breeding ground for anti-vaccination discussions.
- Score: 3.192308005611312
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Vaccination is one of the most impactful healthcare interventions in terms of
lives saved at a given cost, leading the anti-vaccination movement to be
identified as one of the top 10 threats to global health in 2019 by the World
Health Organization. This issue increased in importance during the COVID-19
pandemic where, despite good overall adherence to vaccination, specific
communities still showed high rates of refusal. Online social media has been
identified as a breeding ground for anti-vaccination discussions. In this work,
we study how vaccination discussions are conducted in the discussion forum of
Mumsnet, a United Kingdom based website aimed at parents. By representing
vaccination discussions as networks of social interactions, we can apply
techniques from network analysis to characterize these discussions, namely
network comparison, a task aimed at quantifying similarities and differences
between networks. Using network comparison based on graphlets -- small
connected network subgraphs -- we show how the topological structure
vaccination discussions on Mumsnet differs over time, in particular before and
after COVID-19. We also perform sentiment analysis on the content of the
discussions and show how the sentiment towards vaccinations changes over time.
Our results highlight an association between differences in network structure
and changes to sentiment, demonstrating how network comparison can be used as a
tool to guide and enhance the conclusions from sentiment analysis.
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