BGS Hosted Metadata
River Sentiment Dashboard
The River Sentiment Dashboard displays social media sentiment about more than 450 rivers and other waterbodies in the Thames basin in England alongside data about their ecological status.
You can search for a river or look it up on a map. For each river, the dashboard shows how social media sentiment about the waterbody has shifted between positive and negative over time. The dashboard also shows which basic emotions Twitter users express when talking about the waterbody and which phrases they commonly use in their tweets. Using these data you can explore the link between human wellbeing and river water quality by comparing social media sentiment with ecological status. You can also explore the connection between the common phrases people use to describe the river with the reasons why it is not achieving good ecological status. If you want to compare between different rivers, you can use the colour-coded map at the bottom, which displays overall positive (blue), neutral (yellow), and negative (red) sentiment about all of the waterbodies in the Thames basin.
Simple
- Date (Publication)
- 2022-05-25
- Citation identifier
- 5572544f-42d1-4238-a878-108cdf3a0d0b_resource
- Point of contact
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Organisation name Individual name Electronic mail address Role University of Oxford
Point of contact
- Maintenance and update frequency
- As needed
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GEMET - INSPIRE themes, version 1.0
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water resources
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London
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climate change
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sentiment analysis
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water quality
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twitter
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rivers
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sentiment
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Thames
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- Access constraints
- Other restrictions
- Other constraints
- no limitations
- Use constraints
- Other restrictions
- Other constraints
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no conditions apply
- Spatial representation type
- Text, table
- Language
- English
- Character set
- UTF8
- Topic category
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- Inland waters
- Geoscientific information
- Environment
))
- Begin date
- 2008-01-01
- End date
- 2022-12-31
- Unique resource identifier
- EPSG:27700
- Unique resource identifier
- EPSG:4936
- Distribution format
-
Name Version web page
unknown
- OnLine resource
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Protocol Linkage Name WWW:LINK-1.0-http--link
https://riversentiment.app River Sentiment Dashboard
- Hierarchy level
- application
Conformance result
- Date (Publication)
- 2010-12-08
- Explanation
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This Spatial Data Service set is conformant with the INSPIRE
Implementing Rules for the interoperability of spatial data sets and
services
- Pass
- No
- Statement
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The web-application was developed by a partnership of the University of Oxford, and Thames 21 on the Community Water Management for a Liveable London (CAMELLIA) project led by Imperial College London. The project was supported in 2021-2022 by the University of Oxford's ESRC Impact Acceleration Account.
We mine the Twitter platform for tweets containing the names of 450 waterbodies in the Thames river basin management catchment. The total number of tweets collected is over 4 million tweets with a temporal resolution of January 1st 2008 to the present day. Datasets are aggregated at the water body scale and contain sentiment polarity, emotion detection, and common phrases. Our method for sentiment analysis utilised an augmented version of the NRC Word-Emotion Association Lexicon and a polarized context cluster algorithm in order to determine the sentiment score of a given waterbody. The NRC Word-Emotion Association Lexicon is a dictionary of English words and their associations with eight basic emotions (anger, fear, anticipation, trust, surprise, sadness, joy, and disgust) and two sentiments (negative and positive). The polarised context cluster algorithm gives better results than a simple lookup dictionary approach and functions by clustering groups of words in a tweet (normally around 4) and checks whether valence shifters effect the overall sentiment in the word cluster. Data about the ecological status of waterbodies and the reasons for not achieving good status are from the Environment Agency.
Metadata
- File identifier
- 5572544f-42d1-4238-a878-108cdf3a0d0b XML
- Metadata language
- English
- Parent identifier
-
Water Data Explorer
f05a3593-6f11-4c2e-9be2-da9eab8d64ce
- Hierarchy level
- Series
- Hierarchy level name
-
Series
- Date stamp
- 2024-06-11T14:36:16.876872Z
- Metadata standard name
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ISO 19115:2003/19139
- Metadata standard version
-
1.0
- Metadata author
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Organisation name Individual name Electronic mail address Role University of Oxford
Point of contact
)))