Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review
Scientific interest in the potential of urban green spaces, particularly urban parks, to improve health and well-being is increasing. Traditional research methods such as observations and surveys have recently been complemented by the use of social media data to understand park visitation patterns....
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/11/2/238 |
| _version_ | 1797478807982047232 |
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| author | Gabriele Zabelskyte Nadja Kabisch Zaneta Stasiskiene |
| author_facet | Gabriele Zabelskyte Nadja Kabisch Zaneta Stasiskiene |
| author_sort | Gabriele Zabelskyte |
| collection | DOAJ |
| description | Scientific interest in the potential of urban green spaces, particularly urban parks, to improve health and well-being is increasing. Traditional research methods such as observations and surveys have recently been complemented by the use of social media data to understand park visitation patterns. We aimed to provide a systematic overview of how social media data have been applied to identify patterns of urban park use, as well as the advantages and limitations of using social media data in the context of urban park studies. We used the PRISMA method to conduct a systematic literature analysis. Our main findings show that the 22 eligible papers reviewed mainly used social media data to analyse urban park visitors’ needs and demands, and to identify essential park attributes, popular activities, and the spatial, social, and ecological coherence between visitors and parks. The review allowed us to identify the advantages and limitations of using social media data in such research. These advantages include a large database, real-time data, and cost and time savings in data generation of social media data. The identified limitations of using social media data include potentially biased information, a lack of socio-demographic data, and privacy settings on social media platforms. Given the identified advantages and limitations of using social media data in researching urban park visitation patterns, we conclude that the use of social media data as supplementary data constitutes a significant advantage. However, we should critically evaluate the possible risk of bias when using social media data. |
| first_indexed | 2024-03-09T21:36:50Z |
| format | Article |
| id | doaj.art-f64625e53ebf4110bafd7d62cb31c975 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T21:36:50Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-f64625e53ebf4110bafd7d62cb31c9752023-11-23T20:43:07ZengMDPI AGLand2073-445X2022-02-0111223810.3390/land11020238Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature ReviewGabriele Zabelskyte0Nadja Kabisch1Zaneta Stasiskiene2Institute of Environmental Engineering, Kaunas University of Technology, K. Donelaičio g. 73, LT-44249 Kaunas, LithuaniaGeography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, GermanyInstitute of Environmental Engineering, Kaunas University of Technology, K. Donelaičio g. 73, LT-44249 Kaunas, LithuaniaScientific interest in the potential of urban green spaces, particularly urban parks, to improve health and well-being is increasing. Traditional research methods such as observations and surveys have recently been complemented by the use of social media data to understand park visitation patterns. We aimed to provide a systematic overview of how social media data have been applied to identify patterns of urban park use, as well as the advantages and limitations of using social media data in the context of urban park studies. We used the PRISMA method to conduct a systematic literature analysis. Our main findings show that the 22 eligible papers reviewed mainly used social media data to analyse urban park visitors’ needs and demands, and to identify essential park attributes, popular activities, and the spatial, social, and ecological coherence between visitors and parks. The review allowed us to identify the advantages and limitations of using social media data in such research. These advantages include a large database, real-time data, and cost and time savings in data generation of social media data. The identified limitations of using social media data include potentially biased information, a lack of socio-demographic data, and privacy settings on social media platforms. Given the identified advantages and limitations of using social media data in researching urban park visitation patterns, we conclude that the use of social media data as supplementary data constitutes a significant advantage. However, we should critically evaluate the possible risk of bias when using social media data.https://www.mdpi.com/2073-445X/11/2/238urban green spacessocial media datapark usesystematic reviewbig data |
| spellingShingle | Gabriele Zabelskyte Nadja Kabisch Zaneta Stasiskiene Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review Land urban green spaces social media data park use systematic review big data |
| title | Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review |
| title_full | Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review |
| title_fullStr | Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review |
| title_full_unstemmed | Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review |
| title_short | Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review |
| title_sort | patterns of urban green space use applying social media data a systematic literature review |
| topic | urban green spaces social media data park use systematic review big data |
| url | https://www.mdpi.com/2073-445X/11/2/238 |
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