TY - JOUR
T1 - Great Britain's spatial twitter activity related to ‘fracking’
AU - Bartie, Phil
AU - Varley, Adam
AU - Dickie, Jennifer
AU - Evensen, Darrick
AU - Devine-Wright, Patrick
AU - Ryder, Stacia
AU - Whitmarsh, Lorraine
AU - Foad, Colin
N1 - Funding Information:
This research has been undertaken as part of the ‘The Attitudes to Shale GaS in Space and Time’ (ASSIST) project funded through ESRC and NERC (Grant Ref: NE/R017727/1 ). The authors also thank Twitter Inc. for supporting research through their developer programme.
Publisher Copyright:
© 2023 The Authors
PY - 2023/7
Y1 - 2023/7
N2 - Fracking has proven to be a contentious issue in Great Britain, receiving wide press coverage from the initial sale of exploration and development licences, to the current moratorium. This research tracks the public activity online related to this ‘fracking’ journey by analysing over 317 million geolocated tweets from 2015 to 2020, mapping their location to compare the spatial distribution against the shale gas exploration sites. To spatially normalise the results for population density a chi-squared expectation surface was generated revealing higher than expected levels of interest near the previously active fracking site of Preston New Road and licenced extraction blocks in Lancashire. The data granularity allows for peaks of activity to be identified and topics analysed at higher temporal and spatial resolution than previously possible with more traditional surveys. The paper demonstrates the use of chi-squared expectation surfaces for normalising geotweets and the value of social media spatial-temporal analysis for monitoring local involvement in environmental issues, and for monitoring the changing level of interest across different regions in reaction to political decisions.
AB - Fracking has proven to be a contentious issue in Great Britain, receiving wide press coverage from the initial sale of exploration and development licences, to the current moratorium. This research tracks the public activity online related to this ‘fracking’ journey by analysing over 317 million geolocated tweets from 2015 to 2020, mapping their location to compare the spatial distribution against the shale gas exploration sites. To spatially normalise the results for population density a chi-squared expectation surface was generated revealing higher than expected levels of interest near the previously active fracking site of Preston New Road and licenced extraction blocks in Lancashire. The data granularity allows for peaks of activity to be identified and topics analysed at higher temporal and spatial resolution than previously possible with more traditional surveys. The paper demonstrates the use of chi-squared expectation surfaces for normalising geotweets and the value of social media spatial-temporal analysis for monitoring local involvement in environmental issues, and for monitoring the changing level of interest across different regions in reaction to political decisions.
KW - Fracking
KW - Geolocated tweets
KW - Social media
KW - χ-Squared expectation surface
UR - http://www.scopus.com/inward/record.url?scp=85159041917&partnerID=8YFLogxK
U2 - 10.1016/j.compenvurbsys.2023.101978
DO - 10.1016/j.compenvurbsys.2023.101978
M3 - Article
SN - 0198-9715
VL - 103
JO - Computers, Environment and Urban Systems
JF - Computers, Environment and Urban Systems
M1 - 101978
ER -