Supplementary materials for "Towards a study of everyday geographic information: Bringing the everyday into view"

This repository includes the code, logs and outputs that support the findings of this study published in the paper listed below (De Sabbata et al., forthcoming). The documents include code developed in R, RMarkdown (alongside the HTML files obtained by compiling it) and Python, as well as a document reporting the F1 scores for each one of the two classification models.

De Sabbata, S., Bennett, K., & Gardner, Z. (forthcoming). Towards a study of everyday geographic information: Bringing the everyday into view. Environment and Planning B: Urban Analytics and City Science. https://doi.org/10.1177/23998083231217606