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
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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
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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
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Please send bug reports, patches, and other feedback to
Salvatore Giorgi (sgiorgi@sas.upenn.edu) or H. Andrew Schwartz (has@cs.stonybrook.edu)
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