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Capturing and mapping quality of life using Twitter data
- Zivanovic, Slavica, Martinez, Javier, Verplanke, Jeroen
- GeoJournal 2020 v.85 no.1 pp. 237-255
- automation, case studies, data collection, decision making, people, planning, quality of life, social networks, surveys
- There is an ongoing discussion about the applicability of social media data in scientific research. Moreover, little is known about the feasibility to use these data to capture Quality-of-Life (QoL). This study explores the use of social media in QoL research by capturing and mapping people’s perceptions about their life based on geo-located Twitter data. The methodology is based on a mixed-method approach, combining manual coding of the messages, automated classification, and spatial analysis. Bristol is used as a case study, with a dataset containing 1,374,706 geotagged Tweets. Based on the manual coding results, three QoL domains were analysed. Results show the difference between Bristol wards in number and type of QoL perceptions in every domain, spatial distribution of positive and negative perceptions, and differences between the domains. Furthermore, results from this study are compared to the official QoL survey results from Bristol, statistically and spatially. Overall, three main conclusions are underlined. First, to an extent, Twitter data can be used to evaluate QoL. Second, based on people’s perceptions, there is a difference in QoL between neighbourhoods in Bristol. And, third, Twitter messages can be used to complement QoL surveys, but not act as a proxy for traditional survey results. The main contribution of this study is in recognising the potential Twitter data have in QoL research. This potential lies in producing additional knowledge about QoL that can be placed in a planning context and effectively used to improve the decision-making process and enhance quality-of-life of residents.