This python package provides efficient linguistic feature extraction for text datasets (i.e. datasets with N text instances, in a tabular structure).
For a full overview of the features available, check the overview table, for further details and tutorials check the documentation
Install this package using the current pypi version
python -m pip install elfen
Install this package from source
python -m pip install git+https://github.com/mmmaurer/elfen.git
If you want to use the spacy backbone, download the respective model, e.g. "en_core_web_sm":
python -m spacy download en_core_web_sm
To use wordnet features, download open multilingual wordnet using:
python -m wn download omw:1.4
The extraction of psycholinguistic, emotion/lexicon and semantic features relies on third-party resources such as lexicons. Please refer to the original author's licenses and conditions for usage, and cite them if you use the resources through this package in your analyses.
For an overview which features use which resource, and how to export all third-party resource references in a bibtex
string, consult the documentation.
While all feature extraction functions in this package are written from scratch, the choice of features in the readability and lexical richness feature areas (partially) follows the readability
and lexicalrichness
python packages.
We use the wn
python package to extract Open Multilingual Wordnet synsets.
If you use this package in your work, for now, please cite
@misc{maurer-2025-elfen,
author = {Maurer, Maximilian},
title = {ELFEN - Efficient Linguistic Feature Extraction for Natural Language Datasets},
year = {2025},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/mmmaurer/elfen}},
}