tetano
Editor, Senior Moderator
Citation: Salathé M, Khandelwal S (2011) Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control. PLoS Comput Biol 7(10): e1002199. doi:10.1371/journal.pcbi.1002199
Marcel Salathé*, Shashank Khandelwal
Center for Infectious Disease Dynamics, Department of Biology, Penn State University, University Park, Pennsylvania, United States of America
Abstract Top
There is great interest in the dynamics of health behaviors in social networks and how they affect collective public health outcomes, but measuring population health behaviors over time and space requires substantial resources. Here, we use publicly available data from 101,853 users of online social media collected over a time period of almost six months to measure the spatio-temporal sentiment towards a new vaccine. We validated our approach by identifying a strong correlation between sentiments expressed online and CDC-estimated vaccination rates by region. Analysis of the network of opinionated users showed that information flows more often between users who share the same sentiments - and less often between users who do not share the same sentiments - than expected by chance alone. We also found that most communities are dominated by either positive or negative sentiments towards the novel vaccine. Simulations of infectious disease transmission show that if clusters of negative vaccine sentiments lead to clusters of unprotected individuals, the likelihood of disease outbreaks is greatly increased. Online social media provide unprecedented access to data allowing for inexpensive and efficient tools to identify target areas for intervention efforts and to evaluate their effectiveness.
Author Summary Top
Sentiments about vaccination can strongly affect individual vaccination decisions. Measuring such sentiments - and how they are distributed in a population - is typically a difficult and resource-intensive endeavor. We use publicly available data from Twitter, a popular online social media service, to measure the evolution and distribution of sentiments towards the novel influenza A(H1N1) vaccine during the second half of 2009, i.e. the fall wave of the H1N1 (swine flu) pandemic. We find that projected vaccination rates based on sentiments expressed on Twitter are in very good agreement with vaccination rates estimated by the CDC with traditional phone surveys. Looking at the online social network, we find that both negative and positive opinions are clustered, and that an equivalent level of clustering of vaccinations in a population would strongly increase disease outbreak risks.
Citation: Salathé M, Khandelwal S (2011) Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control. PLoS Comput Biol 7(10): e1002199. doi:10.1371/journal.pcbi.1002199
Editor: Lauren Ancel Meyers, University of Texas at Austin, United States of America
Received: May 10, 2011; Accepted: July 30, 2011; Published: October 13, 2011
Copyright: © 2011 Salathé, Khandelwal. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: MS acknowledges funding from Society in Science: the Branco Weiss fellowship. http://www.society-in-science.org/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002199
Marcel Salathé*, Shashank Khandelwal
Center for Infectious Disease Dynamics, Department of Biology, Penn State University, University Park, Pennsylvania, United States of America
Abstract Top
There is great interest in the dynamics of health behaviors in social networks and how they affect collective public health outcomes, but measuring population health behaviors over time and space requires substantial resources. Here, we use publicly available data from 101,853 users of online social media collected over a time period of almost six months to measure the spatio-temporal sentiment towards a new vaccine. We validated our approach by identifying a strong correlation between sentiments expressed online and CDC-estimated vaccination rates by region. Analysis of the network of opinionated users showed that information flows more often between users who share the same sentiments - and less often between users who do not share the same sentiments - than expected by chance alone. We also found that most communities are dominated by either positive or negative sentiments towards the novel vaccine. Simulations of infectious disease transmission show that if clusters of negative vaccine sentiments lead to clusters of unprotected individuals, the likelihood of disease outbreaks is greatly increased. Online social media provide unprecedented access to data allowing for inexpensive and efficient tools to identify target areas for intervention efforts and to evaluate their effectiveness.
Author Summary Top
Sentiments about vaccination can strongly affect individual vaccination decisions. Measuring such sentiments - and how they are distributed in a population - is typically a difficult and resource-intensive endeavor. We use publicly available data from Twitter, a popular online social media service, to measure the evolution and distribution of sentiments towards the novel influenza A(H1N1) vaccine during the second half of 2009, i.e. the fall wave of the H1N1 (swine flu) pandemic. We find that projected vaccination rates based on sentiments expressed on Twitter are in very good agreement with vaccination rates estimated by the CDC with traditional phone surveys. Looking at the online social network, we find that both negative and positive opinions are clustered, and that an equivalent level of clustering of vaccinations in a population would strongly increase disease outbreak risks.
Citation: Salathé M, Khandelwal S (2011) Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control. PLoS Comput Biol 7(10): e1002199. doi:10.1371/journal.pcbi.1002199
Editor: Lauren Ancel Meyers, University of Texas at Austin, United States of America
Received: May 10, 2011; Accepted: July 30, 2011; Published: October 13, 2011
Copyright: © 2011 Salathé, Khandelwal. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: MS acknowledges funding from Society in Science: the Branco Weiss fellowship. http://www.society-in-science.org/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002199