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

被引:12
作者
Cowie, Sophie [1 ]
Arthur, Rudy [1 ]
Williams, Hywel T. P. [1 ,2 ]
机构
[1] Univ Exeter, Coll Engn Math & Phys Sci, Comp Sci, Exeter EX4 4QE, Devon, England
[2] Alan Turing Inst, 96 Euston Rd, London NW1 2DB, England
基金
英国经济与社会研究理事会; 英国工程与自然科学研究理事会;
关键词
hayfever; social media; pollen; social sensing; crowdsourcing;
D O I
10.3390/s18124434
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页数:11
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