  Continued population growth and urbanization is shifting research to consider
the quality of urban green space over the quantity of these parks, woods, and
wetlands. The quality of urban green space has been hitherto measured by expert
assessments, including in-situ observations, surveys, and remote sensing
analyses. Location data platforms, such as TripAdvisor, can provide people's
opinion on many destinations and experiences, including UGS. This paper
leverages Artificial Intelligence techniques for opinion mining and text
classification using such platform's reviews as a novel approach to urban green
space quality assessments. Natural Language Processing is used to analyze
contextual information given supervised scores of words by implementing
computational analysis. Such an application can support local authorities and
stakeholders in their understanding of and justification for future investments
in urban green space.
