Journal of Public Health | Vol. 36, No. 4, pp. 535 –536 | doi:10.1093/pubmed/fdt128 | Advance Access Publication 12 January 2014

Commentary on ‘Trending now’ Peter John Aspinall Centre for Health Services Studies, University of Kent, George Allen Wing, Canterbury, Kent CT2 7NF, UK Address correspondence to Peter John Aspinall, E-mail: [email protected]

One of the characteristics of new waves of technological innovation is the mixture of hope, hype and speculation about social implications that come in their wake, an exemplar being the revolution of genomic medicine. The use of spin in reporting, the focus on positive trends and the projected transformative effects of such technologies on our lives are commonplace. Reports of the impact of digital media are invariably accompanied by a tsunami of statistics on the growing number of internet, Facebook and Twitter users, all used to champion the benefits of being connected. The hard question of what additional value such technologies are likely to add in specific realms of practice rarely gets posed. Burke-Garcia and Scally attempt to provide this perspective for digital media in the context of global public health. Their peppy and bright but largely uncritical view takes us only so far. That there have already been benefits is undeniable, such as the cited use of social media as a mechanism for study recruitment, follow-up and retention. However, whether some of their broader claims for the future are overstated is perhaps too early to call, their perspective making no mention of the frequently cited harms for public health, such as social media’s role in the dissemination of misinformation, the inappropriate substitution of online information for in-person contact and promotion of high-risk behaviours.1 Let us take from the authors’ top 10 trends the use of digital media for ‘listening in’, but what are we ‘listening in’ to when we access blogs, social media or online forums? Facebook revealed during 2012 that 7.2 – 8.7% of its overall users are fakes, that is, 76 – 83 million people, and some analysts put the figure at 10%. We usually know nothing about who does the posting on these sites and have no means of verifying identities or establishing the credibility of the testimonies. Nor are we able to establish the representativeness of the data in socio-economic or demographic terms and so are constrained in the inferences we can make. Around 35% of Facebook users and 40% of Twitter users are under 35, around 60% of users on both sites being female. Unsought digital ‘listening in’ also raises important issues relating to consent, privacy, ethics and personal data, especially when new data interrogation and processing technologies allow for

an unprecedented level of scrutiny, blurring the boundaries between public and private digital spaces. Even when we have confidence in the ‘listening in’ data, it would seem jejune to argue that the public health sector is well placed in the medium term to exploit the data. Where the amount of material is relatively small, we can easily manually process what we listen into. However, frequently the testimonies are voluminous, running to thousands of posts, tweets and comments which cannot simply be read and turned over in our heads. The ‘listening in’ process has to be automated, yet such technology is in the early phase of development. While some university public health departments are applying machine learning and real-time natural language processing, such as sentiment analysis, to find patterns in large volumes of unstructured free-text information, it seems unrealistic to assume early adoption of these approaches by the wider public health community. Moreover, the yield from such approaches is currently largely unknown, one experimental study’s findings largely confirming what is already known from routinely available data in surveys and structured, patient-reported outcome measures. The medium-term practical gains are more likely to involve the exploitation of textual corpora of known quality and provenance, such as the free text of doctors’ notes or letters, as exemplified by the e-Records Research (CIPHER) and Patient Records Enhancement Programmes. ‘Crowd-sourcing’, another of the top trends, raises similar issues. The media have reported a handful of cases of diagnosis through online sharing within the crowd of illness symptoms, not because of their saliency but because of their exceptionality. Can such cases really be scaled up statistically to something that ‘is becoming commonplace across the globe’? Or is it an example of the power of the anecdote? The utility of Google Trends for real-time surveillance of disease outbreaks has been promoted.2 Yet the decontextualization of such data can equally produce misleading results. This

Peter John Aspinall, Emeritus Reader in Population Health

# The Author 2014. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: [email protected].

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method overestimated the scale of the December 2012 flu outbreak in the USA as searches were probably inflated by media scare stories about the flu.3 Finally, Burke-Garcia and Scally cite the example of digital media connectivity in China, the most populous country in the world (1.36 billion people, one-fifth of the world’s total) and its largest number of internet users (591 million), mainly young, well-educated and urban rather than the vulnerable and the retired. The internet they access is controlled by ‘countless political and administrative bodies, technological word and image filtering tools and human monitors’,4 estimated to involve 2 million people. The Chinese government is also said to employ a quarter of a million people to write pro-government posts in chatrooms, newspaper comment sections and social networking sites, deflecting discussion from sensitive topics. Data subject to such control and infiltration is of insufficient quality for global public health purposes. Around the time of the Beijing Olympic Games, the Chinese government successfully suppressed any online mention of the melamine contamination of formula milk that,

just a few months later, had made 300 000 babies sick. The non-disclosure of rapidly escalating numbers of SARS cases was revealed by letter rather than internet seepage. It seems unlikely that any amount of ‘listening in’ would reveal the real plight of ordinary Chinese people—factory workers, job hunters, migrant workers, the retired, students, mothers and children—living in China’s industrial mega-cities and beleaguered by failing health, systemic poverty and social problems.

References 1 Hamm MP, Chisholm A, Shulhan J. et al. Social media use among patients and caregivers: a scoping review. BMJ Open 2013;3:e002819. doi:10.1136/bmjopen-2013-002819 2 Carniero HA, Mylonakis E. Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clin Infect Dis 2009;49(10): 1557 – 64. 3 Butler D. When Google got flu wrong. Nature 2013;494(7436):155– 6. 4 Lemos G. The End of the Chinese Dream. Why Chinese People Fear the Future. New Haven and London: Yale University Press, 2012.

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