Using VGI and Social Media Data to Understand Urban Green Space: A Narrative Literature Review

• Published in: ISPRS international journal of geo-information 2021-07, Vol.10 (7), p.425
• Main Authors: Cui, Nan, Malleson, Nick, Houlden, Victoria, Comber, Alexis
• Format: Article
• Language: English
• Subjects: Analysis; Bibliometrics; Citations; Cocitation; Data acquisition; Data analysis; Data processing; Digital media; Green infrastructure; Information processing; Keywords; Literature reviews; Open spaces; Priorities; Quality assessment; Quality control; Rural areas; Scientometrics; Search strategies; Social media; social media data; Social networks; Social organization; Tourism; Urban areas; urban green space; Urban planning; volunteered geographical information; Work platforms
• ISSN: 2220-9964; 2220-9964
• DOI: 10.3390/ijgi10070425

Volunteered Geographical Information (VGI) and social media can provide information about real-time perceptions, attitudes and behaviours in urban green space (UGS). This paper reviews the use of VGI and social media data in research examining UGS. The current state of the art is described through the analysis of 177 papers to (1) summarise the characteristics and usage of data from different platforms, (2) provide an overview of the research topics using such data sources, and (3) characterise the research approaches based on data pre-processing, data quality assessment and improvement, data analysis and modelling. A number of important limitations and priorities for future research are identified. The limitations include issues of data acquisition and representativeness, data quality, as well as differences across social media platforms in different study areas such as urban and rural areas. The research priorities include a focus on investigating factors related to physical activities in UGS areas, urban park use and accessibility, the use of data from multiple sources and, where appropriate, making more effective use of personal information. In addition, analysis approaches can be extended to examine the network suggested by social media posts that are shared, re-posted or reacted to and by being combined with textual, image and geographical data to extract more representative information for UGS analysis.