Description:

This interactive map represents the landscape of the literature analyzed during the OID's first research cycle. Each point corresponds to the abstract of one of our sources, positioned in a semantic space based on its content's embedding. The color coding highlights clusters of abstracts that discuss overarching macro-topics, further subdivided into specific, detailed sub-topics.

Use:

The map can be used to efficiently explore the 1,664 sources cited in the Observatory's report, offering insights into the thematic distribution of topics across the analyzed literature. Hover over any point to see the title of the paper that deals with that topic and click to open it in a google search. Use the search bar on the top left to look for words in the sources titles, along with the regional filters and the histogram to filter by region and publication date.

Method:

To create the map we embedded the abstracts of our sources using the all-MiniLM-L6-v2 model from SentenceTranformer. We then used umap for dimensionality reduction into a 2D semantic space and employed hdbscan to identify topic clusters. Finally, we conducted content analysis to derive detailed and macro-topic labels. The datamapplot library was then used to create the visualization.

Author: Giovanni Maggi, OID Data Officer

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