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Tracking the structure and sentiment of vaccination discussions on Mumsnet

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 COVI...

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Autores principales: Silva, Miguel E. P., Skeva, Rigina, House, Thomas, Jay, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657328/
https://www.ncbi.nlm.nih.gov/pubmed/38026264
http://dx.doi.org/10.1007/s13278-023-01155-z
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author Silva, Miguel E. P.
Skeva, Rigina
House, Thomas
Jay, Caroline
author_facet Silva, Miguel E. P.
Skeva, Rigina
House, Thomas
Jay, Caroline
author_sort Silva, Miguel E. P.
collection PubMed
description 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 UK-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 of 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 toward 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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spelling pubmed-106573282023-11-18 Tracking the structure and sentiment of vaccination discussions on Mumsnet Silva, Miguel E. P. Skeva, Rigina House, Thomas Jay, Caroline Soc Netw Anal Min Original Article 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 UK-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 of 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 toward 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. Springer Vienna 2023-11-18 2023 /pmc/articles/PMC10657328/ /pubmed/38026264 http://dx.doi.org/10.1007/s13278-023-01155-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Silva, Miguel E. P.
Skeva, Rigina
House, Thomas
Jay, Caroline
Tracking the structure and sentiment of vaccination discussions on Mumsnet
title Tracking the structure and sentiment of vaccination discussions on Mumsnet
title_full Tracking the structure and sentiment of vaccination discussions on Mumsnet
title_fullStr Tracking the structure and sentiment of vaccination discussions on Mumsnet
title_full_unstemmed Tracking the structure and sentiment of vaccination discussions on Mumsnet
title_short Tracking the structure and sentiment of vaccination discussions on Mumsnet
title_sort tracking the structure and sentiment of vaccination discussions on mumsnet
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657328/
https://www.ncbi.nlm.nih.gov/pubmed/38026264
http://dx.doi.org/10.1007/s13278-023-01155-z
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