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Twitter Influence on UK Vaccination and Antiviral Uptake During the 2009 H1N1 Pandemic Twitter influence on UK vaccination and antiviral uptake during the 2009 H1N1 pandemic Article (Published Version) McNeill, Andrew, Harris, Peter and Briggs, Pam (2016) Twitter influence on UK vaccination and antiviral uptake during the 2009 H1N1 pandemic. Frontiers in Public Health, 4. ISSN 2296-2565 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/id/eprint/61335/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the URL above for details on accessing the published version. Copyright and reuse: Sussex Research Online is a digital repository of the research output of the University. Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available. Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. http://sro.sussex.ac.uk ORIGINAL RESEARCH published: 22 February 2016 doi: 10.3389/fpubh.2016.00026 Twitter influence on UK Vaccination and Antiviral Uptake during the 2009 H1N1 Pandemic Andrew McNeill1 , Peter R. Harris2 and Pam Briggs1* 1 Department of Psychology, Northumbria University, Newcastle Upon Tyne, UK, 2 School of Psychology, University of Sussex, Brighton, UK Objective: Information exchange via Twitter and other forms of social media make pub- lic health communication more complex as citizens play an increasingly influential role in shaping acceptable or desired health behaviors. Taking the case of the 2009–2010 H1N1 pandemic, we explore in detail the dissemination of H1N1-related advice in the UK through Twitter to see how it was used to discourage or encourage vaccine and antiviral uptake. Edited by: Nuria Oliver, Methods: In three stages we conducted (1) an analysis of general content, retweeting Telefonica, Spain patterns, and URL sharing, (2) a discourse analysis of the public evaluation of press Reviewed by: releases and (3) a template analysis of conversations around vaccine and antiviral Caterina Rizzo, uptake, using Protection Motivation Theory (PMT) as a way of understanding how the Istituto Superiore di Sanità, Italy Michele Tizzoni, public weighed the costs and benefits. ISI Foundation, Italy *Correspondence: Results: Network analysis of retweets showed that information from official sources Pam Briggs [email protected] predominated. Analysing the spread of significant messages through Twitter showed that most content was descriptive but there was some criticism of health authorities. Specialty section: A detailed analysis of responses to press releases revealed some scepticism over the This article was submitted to Digital Health, economic beneficiaries of vaccination, that served to undermine public trust. Finally, the a section of the journal conversational analysis showed the influence of peers when weighing up the risks and Frontiers in Public Health benefits of medication. Received: 09 November 2015 Accepted: 08 February 2016 Published: 22 February 2016 Conclusion: Most tweets linked to reliable sources, however Twitter was used to dis- Citation: cuss both individual and health authority motivations to vaccinate. The PMT framework McNeill A, Harris PR and Briggs P describes the ways individuals assessed the threat of the H1N1 pandemic, weighing (2016) Twitter Influence on UK Vaccination and Antiviral Uptake this against the perceived cost of taking medication. These findings offer some valuable during the 2009 H1N1 Pandemic. insights for social media communication practices in future pandemics. Front. Public Health 4:26. doi: 10.3389/fpubh.2016.00026 Keywords: social media, pandemic, influenza, public health, H1N1 virus Frontiers in Public Health | www.frontiersin.org 1 February 2016 | Volume 4 | Article 26 McNeill et al. Twitter Influence on Vaccination and Antiviral Uptake INTRODUCTION a useful source of data for understanding public reactions dur- ing pandemics. Furthermore, such sentiment-coded data can be Pandemics pose a challenge to public health officials, who need used to predict the uptake of vaccines in specific areas depending to coordinate a swift and effective communication strategy so on the level of sentiment expressed in tweets from that area (9). that the general public can be informed about the risks of the Information about the vaccine tended to be shared between users pandemic and the appropriate behavioral response to those risks. who shared similar sentiment (9) and having larger numbers of A failure to communicate effectively at such times can be very opinionated friends on Twitter tended to inhibit expressing senti- serious (1). In this paper, we add to the body of knowledge about ment about the vaccine (10). However, the presence of negative the role of social media in communicating information about a sentiment in tweets about the vaccine tended to breed future pandemic, focusing upon the UK response to the H1N1 virus. negative sentiment from other connected users, showing the H1N1 was an influenza virus that originated in Mexico. In contagious nature of negative sentiment (10). Other research (11) April 2009, the World Health Organisation (WHO) announced showed that Twitter users had a preference for sharing websites that they had detected the rapid spread of this virus and public that contained reliable information (e.g., sites like BBC, WHO, health bodies worldwide began to make preparations (2). During or CDC) although in some circumstances unreliable information this period, social media sites were used to communicate infor- was prominent. Few other studies specifically study the content mation and thoughts about the pandemic and how to deal with of Twitter messages during pandemics, although several studies it, which meant that, for the first time, the pandemic could be have pointed out the value of Twitter for predicting flu trends 12( , explored through the analysis of social media networks in gen- 13) in the vein of other research that attempts to use large datasets eral, and the analysis of Twitter in particular (3). Indeed, Chew to predict societal trends. and Eysenbach (3) described the H1N1 pandemic as occurring Unpacking communication practices on Twitter are not easy in the “Age of Twitter.” as the messages are limited to 140 characters and this makes The control of health messages during a pandemic has never it difficult to get any sense of nuance. For example, sentiment lain entirely in the hands of health professionals. Word of mouth analysis can be misleading as jokes or sarcasm can easily be has always been important and the press and broadcast news misinterpreted. In studies exploring the links shared by others, media have been shown to have a strong role in influencing public the presence of parody is known to complicate the interpretation opinion and behavior during earlier pandemics, such as SARS of data (11). As a consequence, we argue, it is important to supple- (4, 5). While the influence of mainstream media has continued ment large-scale automated analyses with qualitative approaches to be a focus for research (6, 7), a number of recent studies have that can explore nuance and interpret subtleties that cannot be explored the democratization of influence that comes with Twitter otherwise detected. To a certain extent, this mixed methods and other forms of social media (8). approach was adopted in the Chew and Eysenbach paper, which This “democratization” brings both challenges and oppor- provides a model for what can be achieved by a big data, little data tunities for the health community. For example, consider the combination. However, the goals of the study we report here are roll-out of public vaccination programs. On the one hand, there rather different. are new opportunities for health authorities to engage directly As we noted earlier, compliance with official guidance can with the general public or to target vulnerable groups with care- be crucial during a pandemic, but the information and advice fully customized information about appropriate vaccination or disseminated by health authorities can be contested and social antiviral use. On the other hand, there are new and plentiful media has provided a platform for such activity. A major goal of opportunities for dissent. For example, antivaccination groups, our current study, then, is to use Twitter data to better understand who may previously have had a limited sphere of influence, public discourse in the wake of a sequence of key UK-based gain a new voice in social media and acquire the opportunity health announcements about the 2009 H1N1 pandemic. Here, to be heard alongside official health advice. Private concerns we are focusing upon the responses made by the UK public to an about vaccination can be spread to thousands of followers in orchestrated series of health press-releases and directives and also an instant – increasing for many the perception of the risk of exploring the ways in which vaccination and antiviral advice was vaccinating. promoted or contested throughout the network. The role of Twitter in the 2009–2010 H1N1 (“swine flu”) In the first part of the paper, we ask simply how the UK data pandemic has been studied in some detail, in part because the compare to the global data as described by Chew and Eysenbach pandemic emerged just at a time when Twitter (established in (3) and also note the variation in Twitter activity around the 2006) was becoming popular. The largest study is that of Chew time of seven key public announcements.
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