Tethne: Bibliographic Network Analysis in Python


Tethne provides tools for easily parsing and analyzing bibliographic data in Python. The primary emphasis is on working with data from the ISI Web of Science database, and providing efficient methods for modeling and analyzing citation-based networks. Future versions will include support for PubMed, Scopus, and other databases.

As of v0.3, Tethne is beginning to include methods for incorporating data from the JSTOR Data-for-Research service, and MALLET topic modeling.

Tethne relies on NetworkX for graph classes, and leverages its network analysis algorithms. You can visualize networks produced with Tethne in Cytoscape or Gephi.

To get started, consult the tutorial. For support, visit our GitHub repository.


Tethne is developed by the ASU Digital Innovation Group (DigInG), part of the Laubichler Lab in the Center for Biology & Society, School of Life Sciences.

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 2011131209, and NSF Doctoral Dissertation Research Improvement Grant No. 1256752.

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