.. 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) `_.