Visualizing an image network without rendering files: the development of a methodological framework combining user hashtags with computer vision labe…

2022

This article presents a method for visualizing networks of geolocated images without rendering the image files on the network. The path I followed to develop this method is the result of an intensive "data sprint" which took place during the University of Amsterdam Digital Methods Initiative Summer School 2021. During the data sprint, I developed a methodological framework to generate a network of Twitter geolocated images combining the hashtags twitted with the images and the Google Cloud Vision API best single expression to describe each image (BestGueesLabel). Considering the limitations of working with a massive amount of image data and the computational memory required to generate netw…