@choo: Tracking Pollen and Hayfever in the UK Using Social Media
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 su...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/18/12/4434 |
| _version_ | 1798038176412991488 |
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| author | Sophie Cowie Rudy Arthur Hywel T. P. Williams |
| author_facet | Sophie Cowie Rudy Arthur Hywel T. P. Williams |
| author_sort | Sophie Cowie |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T21:36:39Z |
| format | Article |
| id | doaj.art-74f0f53632cd43e7b258079cca05455f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:36:39Z |
| publishDate | 2018-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-74f0f53632cd43e7b258079cca05455f2022-12-22T04:01:44ZengMDPI AGSensors1424-82202018-12-011812443410.3390/s18124434s18124434@choo: Tracking Pollen and Hayfever in the UK Using Social MediaSophie Cowie0Rudy Arthur1Hywel T. P. Williams2Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QE, UKComputer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QE, UKComputer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QE, UKAllergic 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.https://www.mdpi.com/1424-8220/18/12/4434hayfeversocial mediapollensocial sensingcrowdsourcing |
| spellingShingle | Sophie Cowie Rudy Arthur Hywel T. P. Williams @choo: Tracking Pollen and Hayfever in the UK Using Social Media Sensors hayfever social media pollen social sensing crowdsourcing |
| title | @choo: Tracking Pollen and Hayfever in the UK Using Social Media |
| title_full | @choo: Tracking Pollen and Hayfever in the UK Using Social Media |
| title_fullStr | @choo: Tracking Pollen and Hayfever in the UK Using Social Media |
| title_full_unstemmed | @choo: Tracking Pollen and Hayfever in the UK Using Social Media |
| title_short | @choo: Tracking Pollen and Hayfever in the UK Using Social Media |
| title_sort | choo tracking pollen and hayfever in the uk using social media |
| topic | hayfever social media pollen social sensing crowdsourcing |
| url | https://www.mdpi.com/1424-8220/18/12/4434 |
| work_keys_str_mv | AT sophiecowie chootrackingpollenandhayfeverintheukusingsocialmedia AT rudyarthur chootrackingpollenandhayfeverintheukusingsocialmedia AT hyweltpwilliams chootrackingpollenandhayfeverintheukusingsocialmedia |