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tethne 0.3.0-alpha

Library for analyzing bibliographic data

Package Documentation

Latest Version: 0.6.3.3-beta

Tethne is a script for analyzing bibliographic data. The primary emphasis is on parsing
and analyzing citation data from the Web of Science. Future versions will support data
from PubMed, Scopus, and other scholarly databases. Tethne can be used to generate and
analyze a variety of networks, such as bibliographic coupling, citation, author-paper,
and co-author networks, using [NetworkX]http://networkx.github.io/)

For more information, see the Tethne `website <https: github.com="" diging="" tethne="">`_ and
`documentation <http: diging.github.io="" tethne="" api=""/>`_ (under development).

Requirements
===========

* `Python 2.7 <http: www.python.org=""/>`_
* `NetworkX <http: networkx.github.io=""/>`_
* `ElementTree <http: docs.python.org="" 2="" library="" xml.etree.elementtree.html="">`_

Questions?
=======

Ask `Erick <https: cbs.asu.edu="" gradinfo="" ?page_id="49">`_

Contributors
==========

* `erickpeirson <http: github.com="" erickpeirson="">`_
* `aabaker99 <http: github.com="" aabaker99="">`_
* `rsubra13 <http: github.com="" rsubra13="">`_

License
=======

Tethne is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

Tethne is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
`GNU General Public License <http: www.gnu.org="" licenses=""/>` for more details.

About
======

Tethne is developed by the `ASU Digital Innovation Group (DigInG) <http: devo-evo.lab.asu.edu="" diging="">`_,
part of the `Laubichler Lab <http: devo-evo.lab.asu.edu="">`_ 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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