Difference between revisions of "Extra:citation visualizations"

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(Existing tools for visualizing and data-analytics of citation networks)
(General Visualization Tools (that could be used for citation networks))
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==General Visualization Tools (that could be used for citation networks)==
 
==General Visualization Tools (that could be used for citation networks)==
* [http://python.org/ Python]
+
* [http://python.org/ Python]: General-purpose high-level programming language.
 
** [http://matplotlib.org/ matplotlib] for generalized plotting
 
** [http://matplotlib.org/ matplotlib] for generalized plotting
 
** [iPython network citation example]
 
** [iPython network citation example]
 
** [http://networkx.github.io/ NetworkX]: Package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
 
** [http://networkx.github.io/ NetworkX]: Package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
 +
** [https://snap.stanford.edu/snappy/ Snap.py]: Python interface to SNAP, providing high-performance node/network layout and visualization.
 +
* [https://d3js.org/ D3.js]: JavaScript libraries for visualization. Well-suited to interactive web-based analytic tools.
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** [https://github.com/d3/d3/wiki/Gallery Gallery]
  
 
==Additional Information==
 
==Additional Information==

Revision as of 18:13, 16 November 2016

Existing tools for visualizing and data-analytics of citation networks

  • VOSviewer: Tool for constructing and visualizing bibliometric networks. Offers text mining functionality that can be used to construct and visualize co-occurrence networks of important terms extracted from a body of scientific literature.
Scimaplarge.jpg

General Visualization Tools (that could be used for citation networks)

  • Python: General-purpose high-level programming language.
    • matplotlib for generalized plotting
    • [iPython network citation example]
    • NetworkX: Package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
    • Snap.py: Python interface to SNAP, providing high-performance node/network layout and visualization.
  • D3.js: JavaScript libraries for visualization. Well-suited to interactive web-based analytic tools.

Additional Information