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Automated Citation Network Analysis for Research Papers

network analysis citation tracking academic research graph theory
Prompt
Create a Python script using NetworkX and Pandas that can parse a large corpus of scientific PDFs to construct a citation network graph. The script should extract citation metadata, build a directed graph representing academic paper relationships, and calculate network metrics like centrality, clustering coefficient, and influence scores. Include functionality to visualize the network using Plotly and generate a comprehensive JSON report of key network characteristics, with special attention to handling complex citation formats across different scientific domains.
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Pro
Python
Science
Mar 2, 2026

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Use Cases
  • Mapping citation networks in a specific research area.
  • Identifying key papers and authors in a field.
  • Analyzing trends in research impact over time.
Tips for Best Results
  • Regularly update your citation database for accurate analysis.
  • Use visualizations to communicate findings effectively.
  • Combine citation analysis with qualitative reviews for depth.

Frequently Asked Questions

What is the Automated Citation Network Analysis for Research Papers?
It analyzes citation networks to uncover relationships between research papers.
How does this tool assist in literature reviews?
By visualizing citation patterns and identifying influential works.
Can it be used for any academic discipline?
Yes, it is applicable across various fields of research.
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