The Grass is Greener on the Other Side

Abstract

Green spaces are believed to improve the well-being of users in urban areas. While there are urban research exploring the emotional benefits of green spaces, these works are based on user surveys and case studies, which are typically small in scale, intrusive, time-intensive and costly. In contrast to earlier works, we utilize a non-intrusive methodology to understand green space effects at large-scale and in greater detail, via digital traces left by Twitter users. Using this methodology, we perform an empirical study on the effects of green spaces on user sentiments and emotions in Melbourne, Australia and our main findings are: (i) tweets in green spaces evoke more positive and less negative emotions, compared to those in urban areas; (ii) each season affects various emotion types differently; (iii) there are interesting changes in sentiments based on the hour, day and month that a tweet was posted; and (iv) negative sentiments are typically associated with large transport infrastructures such as train interchanges, major road junctions and railway tracks. The novelty of our study is the combination of psychological theory, alongside data collection and analysis techniques on a large-scale Twitter dataset, which overcomes the limitations of traditional methods in urban research.

Visitors to urban greenspace have higher sentiment and lower negativity on Twitter

“…Possible explanations for this trend are anticipation for the park visit, meeting friends on the way, or perhaps relief due to leaving work and heading to a more enjoyable location. Recent work found that the emotion of anticipation increases in greenspaces (Lim et al, ); further investigation is merited to better understand the temporal dynamics of anticipation and its relationship with nature contact.…”

“…In the present study, we use location‐enabled data from social media to observe individuals at a level of geographical precision that indicates actual contact with greenspace and biodiversity. Previous studies analysing tweets in urban greenspace have studied comparative well‐being across a city, emotional changes across seasons, and different ways of analysing the emotional content of tweets (Lim et al, ; Plunz et al, ; Roberts et al, ).…”

Beyond Spatial Proximity—Classifying Parks and Their Visitors in London Based on Spatiotemporal and Sentiment Analysis of Twitter Data

“…At the same time, Twitter data analysis is mostly limited in data accessibility, thereby, once the required data is available, the analysis can be performed on scales ranging from intra-urban to even global for any period ranging from a few hours to several years. Recent developments in Geographic Information Systems (GIS)-based social media analysis offer the possibility to explore spatial, temporal and even affective aspects of users' behavior, even for public spaces and park visits [28][29][30]47,48]. However, some of these analyses still have limitations due to the manual interpretation of only a relatively low number of social media posts.…”

“…After the algorithm assigned a value to each of these new attributes, we compared whether there is a difference between park tweets and non-park tweets. Based on previous studies (e.g., [47]) the hypothesis was that park tweets could be more positive. However, our results only partially confirm this.…”

Visual features influence thought content in the absence of overt semantic information

“…It has recently been shown that the physical environment can also influence thought content and valence (Lim et al, 2018;MacKerron & Mourato, 2013;Schertz et al, 2018). This may be one pathway for these effects, as thoughts in turn can influence mood and behavior (Killingsworth & Gilbert, 2010;Pennebaker & Beall, 1986).…”