Do Semantic Vectors Contain Traces of Biophilic Connections Between Nature and Mental Health?

Abstract

Natural environments have positive effects on mental health, but the nature of this relationship requires further understanding. There may be psychosocial aspects of this relationship that are reflected in the semantic structure of language. Natural language processing methods provide a tool to explore this possibility. In this study, machine learning-derived vector representations of words were provided by a neural network-based language model. This was combined with statistical analyses to test whether nature-related words have particularly strong positive versus negative connections to mental health. Statistically significant associations were indeed found between a range of nature-related words and positive-versus-negative word pairs related to mental health. The results thus confirm a semantic connection between nature and mental health as represented using computational methods trained on language usage. This raises the possibility that semantic associations could play a role in nature's influence on mental health, for instance through appraisal processes. The results provide a proof of principle of a methodological approach that could be used to further probe hypotheses on nature and well-being. Finally, the current results provide information on relationships between specific aspects of nature environments and mental health that may be of use to future research.