Next Article in Journal
Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization
Previous Article in Journal
A Path Loss and Shadowing Model for Multilink Vehicle-to-Vehicle Channels in Urban Intersections
Previous Article in Special Issue
UISTD: A Trust-Aware Model for Diverse Item Personalization in Social Sensing with Lower Privacy Intrusion
Open AccessArticle

@choo: Tracking Pollen and Hayfever in the UK Using Social Media

Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QE, UK
The Alan Turing Institute, 96 Euston Road, London NW1 2DB, UK
Author to whom correspondence should be addressed.
Sensors 2018, 18(12), 4434;
Received: 26 October 2018 / Revised: 3 December 2018 / Accepted: 10 December 2018 / Published: 14 December 2018
(This article belongs to the Special Issue Social Sensing)
Allergic rhinitis (hayfever) affects a large proportion of the population in the United Kingdom. Although relatively easily treated with medication, symptoms nonetheless have a substantial adverse effect on wellbeing during the summer pollen season. Provision of accurate pollen forecasts can help sufferers to manage their condition and minimise adverse effects. Current pollen forecasts in the UK are based on a sparse network of pollen monitoring stations. Here, we explore the use of “social sensing” (analysis of unsolicited social media content) as an alternative source of pollen and hayfever observations. We use data from the Twitter platform to generate a dynamic spatial map of pollen levels based on user reports of hayfever symptoms. We show that social sensing alone creates a spatiotemporal pollen measurement with remarkable similarity to measurements taken from the established physical pollen monitoring network. This demonstrates that social sensing of pollen can be accurate, relative to current methods, and suggests a variety of future applications of this method to help hayfever sufferers manage their condition. View Full-Text
Keywords: hayfever; social media; pollen; social sensing; crowdsourcing hayfever; social media; pollen; social sensing; crowdsourcing
Show Figures

Figure 1

MDPI and ACS Style

Cowie, S.; Arthur, R.; Williams, H.T.P. @choo: Tracking Pollen and Hayfever in the UK Using Social Media. Sensors 2018, 18, 4434.

AMA Style

Cowie S, Arthur R, Williams HTP. @choo: Tracking Pollen and Hayfever in the UK Using Social Media. Sensors. 2018; 18(12):4434.

Chicago/Turabian Style

Cowie, Sophie; Arthur, Rudy; Williams, Hywel T.P. 2018. "@choo: Tracking Pollen and Hayfever in the UK Using Social Media" Sensors 18, no. 12: 4434.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop