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academic_data_viz's Introduction

Academic Data Visualization and Analysis

Objectives:

  1. Generate Field of Study(Fos) heirarchy from Microsoft Academic Graph(https://www.microsoft.com/en-us/research/project/microsoft-academic-graph/).
  2. Use heriarchy to replicate Fos Score, from original publication(https://dl.acm.org/doi/10.1145/3041021.3053064).
  3. Query Microsoft Academic Knowledge API for data on two selected fields of study.
  4. Create visualizations from calculated Fos scores for related fields of study and most relavent authors.
  5. Generate more insights from queried data (Planned).

Sample Visualizations:

Top related fields:

Top Fields

Top authors:

Top Authors

Using the repository:

1.fos_hierarchy.py to generate Field of study Hierarchy in fos.pkl

  • Files in fos_list/ may need to be updated to match latest format on MAG database.
  • Fos level lists in fos_list/ were created by directly querying Microsoft Academic Knowledge API.

2.main.py to generate visualizations.

  • First calls query_MAG.py to send a get request to MAK API.
  • Calls fos_calc.py to generate fos scores for each paper.
  • Calls plot_graph.py to draw visualizations.

3.fos_print.py to print generated fos.pkl heirarchy file to check integrity.

You should generate your own API KEY for Microsoft Academic Knowlegde API before using the code at https://www.microsoft.com/en-us/research/project/academic-knowledge/

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