The present data visualization tool aims at the understanding on how Machine Learning spreads around in the academic world. Indeed, the insights gotten from the analysis of the diffusion on Machine Learning can help us identify the main boosters of this field so that policy makers can in time, boost the main producers of innovation. This chain effect could potentially improve the quality of different investigations by redirecting budget allocations, can help limit the extend of AI to avoid harm in the communities, and even create a deeper impact by proposing policies that benefit from the networks created in the production of AI.
The complete sourcecode is found in this repository.
The development has been done using Python, mainly using Dash and Plotly for the visualizations and networkx to analyse the graphs created.
The data can be downloaded from https://docs.openalex.org/. For this project the institutions were downloaded, as well as the works data dump, filtering by publications related to Artificial Intelligence. The data was uploaded to a local Mongo Database for easy handling.
The packages needed for development are found in requirements.txt
The deployed project is found in: http://pythonprojectel.pythonanywhere.com/