Mining, Shaping, Visualizing, and Interpreting Instagram Hypertextual Networks of Freight Train Graffiti Communalities in North America Using Machine Learning Custom Models and Graphology

Academic article published in UXUC-User Experience and Urban Creativity (Portugal). Explains in detail the design, architecture, and analysis derived from the integration of the Python data extraction bot (idmb) and the Web-based Data Visualization Interface (DVI).

The document describes the processing of a relational cluster of Instagram posts associated with transnational freight graffiti. It details the use of computer vision convolutional models to classify pictorial styles on cargo cars, mapping relational profiles using structural centrality metrics with SigmaJS and Graphology.