Metadata-Version: 2.1
Name: textnets
Version: 0.4.11
Summary: Automated text analysis with networks
Home-page: https://textnets.readthedocs.io
Author: John D. Boy
Author-email: jboy@bius.moe
License: GNU General Public License v3
Description: =====================================
        Textnets: text analysis with networks
        =====================================
        
        .. image:: https://travis-ci.org/jboynyc/textnets.svg?branch=master
           :target: https://travis-ci.org/jboynyc/textnets
           :alt: Travis-CI Status
        
        .. image:: https://readthedocs.org/projects/textnets/badge/?version=stable
           :target: https://textnets.readthedocs.io/en/stable/?badge=stable
           :alt: Documentation Status
        
        .. image:: https://anaconda.org/conda-forge/textnets/badges/installer/conda.svg
           :target: https://anaconda.org/conda-forge/textnets
           :alt: Install with conda
        
        .. image:: https://joss.theoj.org/papers/10.21105/joss.02594/status.svg
           :target: https://doi.org/10.21105/joss.02594
           :alt: Published in Journal of Open Source Software
        
        **textnets** represents collections of texts as networks of documents and
        words. This provides novel possibilities for the visualization and analysis of
        texts.
        
        .. figure:: https://textnets.readthedocs.io/en/dev/_static/impeachment-statements.svg
           :alt: Bipartite network graph
        
           Network of U.S. Senators and words used in their official statements
           following the acquittal vote in the Senate impeachment trial (`source
           <https://www.jboy.space/blog/enemies-foreign-and-partisan.html>`_).
        
        This is a Python implementation of `Chris Bail's textnets package for R`_. It
        is free software under the terms of the GNU General Public License v3.
        
        .. _`Chris Bail's textnets package for R`: https://github.com/cbail/textnets/
        
        The idea underlying **textnets** is presented in this paper:
        
          Christopher A. Bail, "`Combining natural language processing and network
          analysis to examine how advocacy organizations stimulate conversation on social
          media`__," *Proceedings of the National Academy of Sciences of the United States
          of America* 113, no. 42 (2016), 11823–11828, doi:10.1073/pnas.1607151113.
        
        __ https://doi.org/10.1073/pnas.1607151113
        
        Features
        --------
        
        **textnets** builds on the state-of-the-art library `spacy`_ for
        natural-language processing and `igraph`_ for network analysis. It uses the
        `Leiden algorithm`_ for community detection, which is able to perform community
        detection on the bipartite (word–group) network.
        
        .. _`Leiden algorithm`: https://arxiv.org/abs/1810.08473
        .. _`igraph`: http://igraph.org/python/
        .. _`spacy`: https://spacy.io/
        
        **textnets** seamlessly integrates with `pandas`_ and other parts of Python's
        excellent `scientific stack`_. That means that you can use **textnets** in
        Jupyter notebooks to analyze and visualize your data!
        
        .. _`pandas`: https://pandas.io/
        .. _`scientific stack`: https://numfocus.org/
        
        **textnets** is easily installable using the ``conda`` and ``pip`` package
        managers.
        
        Read `the documentation <https://textnets.readthedocs.io>`_ to find out more
        about the package's features.
        
        Citation
        --------
        
        Using **textnets** in a scholarly publication? Please cite this paper:
        
        .. code-block:: bibtex
        
           @article{Boy2020,
             author = {John D. Boy},
             title = {textnets},
             subtitle = {A {P}ython Package for Text Analysis with Networks},
             journal = {Journal of Open Source Software},
             volume = {5},
             number = {54},
             pages = {2594},
             year = {2020},
             doi = {10.21105/joss.02594},
           }
        
        Learn More
        ----------
        
        ==================  =============================================
        **Documentation**   https://textnets.readthedocs.io/
        **Repository**      https://github.com/jboynyc/textnets
        **Issues & Ideas**  https://github.com/jboynyc/textnets/issues
        **Conda-Forge**     https://anaconda.org/conda-forge/textnets
        **PyPI**            https://pypi.org/project/textnets/
        **DOI**             `10.21105/joss.02594 <https://doi.org/10.21105/joss.02594>`_
        **Archive**         `10.5281/zenodo.3866676 <https://doi.org/10.5281/zenodo.3866676>`_
        ==================  =============================================
        
Keywords: textnets
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Sociology
Requires-Python: >=3.7
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: doc
