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DLATK is an end to end human text analysis package, specifically suited for social media and social scientific applications. It is written in Python 3 and developed by the World Well-Being Project at the University of Pennsylvania and Stony Brook University.

Project Description


DLATK v1.1
----------

This package offers end to end text analysis: feature extraction, part-of-speech tagging, correlation,
mediation, prediction / classification, dimensionality reduction and clustering, and wordcloud visualization. For more information please visit:

* http://dlatk.wwbp.org
* https://www.github.com/dlatk/dlatk
* http://wwbp.org

CITATION
--------

If you use DLATK in your work please cite the following paper:

@InProceedings{DLATKemnlp2017,
author = "Schwartz, H. Andrew
and Giorgi, Salvatore
and Sap, Maarten
and Crutchley, Patrick
and Eichstaedt, Johannes
and Ungar, Lyle",
title = "DLATK: Differential Language Analysis ToolKit",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
year = "2017",
publisher = "Association for Computational Linguistics",
pages = "55--60",
location = "Copenhagen, Denmark",
url = "http://aclweb.org/anthology/D17-2010"
}

CONTACT
-------

Please send bug reports, patches, and other feedback to

Salvatore Giorgi (sgiorgi@sas.upenn.edu) or H. Andrew Schwartz (has@cs.stonybrook.edu)

Release History

This version
History Node

1.1.4

History Node

1.1.3

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1.1.2

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1.1.0

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1.0.0

History Node

0.6.1

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File Name & Hash SHA256 Hash Help Version File Type Upload Date
dlatk-1.1.4.tar.gz
(20.6 MB) Copy SHA256 Hash SHA256
Source Jan 11, 2018

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