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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:



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

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 = ""


Please send bug reports, patches, and other feedback to

Salvatore Giorgi ( or H. Andrew Schwartz (

Project details

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