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Complete network construction and analysis using Python. Includes: Preferential Attachment, Centrality Measures, Degree Distribution, and Rich-Club

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Co-Authorship-Network-Analysis

Complete network construction and analysis using Python. Includes: Preferential Attachment, Centrality Measures, Degree Distribution, and Rich-Club

The Jupyter Notebook code contains everything you need to create a co-authorship network and analyze it using Python. The Python metdata data code enables you to create an ID list for the authors, papers, and then a Author-Paper ID list that is used in the analysis code book. I have also provided an example of the results.

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Complete network construction and analysis using Python. Includes: Preferential Attachment, Centrality Measures, Degree Distribution, and Rich-Club

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