.. DLATK documentation master file, created by
sphinx-quickstart on Wed Sep 7 15:59:11 2016.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Differential Language Analysis ToolKit
--------------------------------------
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. It contains:
* feature extraction
* part-of-speech tagging
* correlation
* prediction and classification
* mediation
* dimensionality reduction and clustering
* wordcloud visualization
DLATK can utilize:
- `HuggingFace `_ for transformer language models
- `Mallet `_ for creating LDA topics
- `Stanford Parser `_
- `CMU's TweetNLP `_
- `pandas `_ dataframe output
Getting Started
---------------
.. toctree::
:maxdepth: 1
install
Github Repo
Getting started in Colab
tutorials
datasets
dlatkinterface_ordered
papers
Citations
---------
If you use DLATK in your work please cite the following `paper `_:
.. code-block:: bash
@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"
}
More Information
----------------
* `DLATK GitHub page `_
* `DLATK at DockerHub `_
* `World Well-Being Project `_
* `Human Language Analysis Beings (HLAB) at Stony Brook `_
* `Computational Psychology & Well-Being Lab (CPWB) at Stanford University `_
* :doc:`modules`
* :doc:`changelog`
DLATK is licensed under a `GNU General Public License v3 (GPLv3) `_.