eMFDscore is a library for the fast and flexible extraction of various moral information metrics from textual input data. eMFDscore is built on spaCy for faster execution and performs minimal preprocessing consisting of tokenization, syntactic dependency parsing, lower-casing, and stopword/punctuation/whitespace removal. eMFDscore lets users score documents with multiple Moral Foundations Dictionaries and provides various metrics for analyzing moral information. We also encourage users to check out eMACDscore, an alternative moral mining tool from our lab that adopts the theoretical perspective of Morality as Cooperation.
When using eMFDscore, please consider giving this repository a star (top right corner) and citing the following article:
Hopp, F. R., Fisher, J. T., Cornell, D., Huskey, R., & Weber, R. (2020). The extended Moral Foundations Dictionary (eMFD): Development and applications of a crowd-sourced approach to extracting moral intuitions from text. Behavior Research Methods, https://doi.org/10.3758/s13428-020-01433-0
eMFDscore is dual-licensed under GNU GENERAL PUBLIC LICENSE 3.0, which permits the non-commercial use, distribution, and modification of the eMFDscore package. Commercial use of the eMFDscore requires an application.
If you have any questions and/or require additional assistance with running the package, feel free to connect directly with the current package maintainer, Musa Malik, via their LinkedIn.
eMFDscore requires a Python installation (v3.11+). If your machine does not have Python installed, we recommend installing Python by downloading and installing either Anaconda or Miniconda for your OS.
For best practises, we recommend installing eMFDscore into a virtual conda environment. Hence, you should first create a virtual environment by executing the following command in your terminal:
$ conda create -n emfd python=3.11
Once Anaconda/Miniconda is installed activate the env via:
$ source activate emfd
Next, you must install spaCy, which is the main natural language processing backend that eMFDscore is built on:
$ conda install -c conda-forge spacy
$ python -m spacy download en_core_web_sm
Finally, you can install eMFDscore by copying, pasting, and executing the following command:
pip install https://github.com/medianeuroscience/emfdscore/archive/master.zip
eMFDscore can also be run in google colab. All you need to do is add these lines to the beginning of your notebook, execute them, and then restart your runtime:
!pip install https://github.com/medianeuroscience/emfdscore/archive/master.zip
You can then use eMFDscore as a regular python library.