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#hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK

Quincey, ED; Kyriacou, T; Pantin, T; (2016) #hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK. In: Kostkova, P and Grasso, F and Castillo, C, (eds.) DH '16: Proceedings of the 6th International Conference on Digital Health Conference. (pp. pp. 85-89). ACM: Association for Computing Machinery Green open access

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Abstract

This paper describes a longitudinal study that has collected and analysed over 512,000 UK geolocated tweets over 2 years from June 2012 that contained instances of the words “hayfever” and “hay fever”. The results indicate that the temporal distribution of the tweets collected in 2014 correlates strongly (r=0.97, p<0.01) with incidents of hay fever reported by the Royal College of General Practitioners (RCGP) in the same year. An analysis of the content of the tweets indicates that users are self-reporting common, often severe symptoms as well as the uses of medication. We conclude that hay fever related tweets provide a real-time, free and easily accessible source of data at a finer level of granularity than currently available data sets. The implications for researchers, health professionals and sufferers are also discussed.

Type: Proceedings paper
Title: #hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK
ISBN-13: 978-1-4503-4224-7
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/2896338.2896342
Publisher version: http://dl.acm.org/citation.cfm?id=2896338
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Hay fever, Hayfever, allergic rhinitis, Social Media, twitter.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction
URI: https://discovery.ucl.ac.uk/id/eprint/10120922
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