Easy-to-use, high-quality identification of generic framing dimensions in English news articles
APACHE-2.0 License
A single-label classifier for universal framing dimensions in news articles on political topics. These dimensions and their respective short descriptions are:
We are currently working on a paper detailing these dimensions and their conceptualization in more detail.
Create python environment, for example with conda. Python 3.8 or later is supported.
conda create --yes -n NewsFrames python=3.8
conda activate NewsFrames
Install:
pip install NewsFrames
from NewsFrames import Classifier
classifier = Classifier()
results = classifier.predict(["Executives at the British software company Autonomy mischaracterised revenues from clients including Tottenham Hotspur, the Serious Fraud Office and the BBC to inflate software sales figures before a disastrous 8bn acquisition by the US firm Hewlett-Packard, Londons high court has heard."])
print(results)
You can use the attribute_mode
parameter to get predictions for the individual
attributes (attribute_mode="withattributes"
) or only whether the respective dimension
is present or not (attribute_mode="withoutattributes"
). The default is
withattributes
.
classifier = Classifier(attribute_mode="withoutattributes")
Thanks to Tilman Hornung for preparing and analyzing the datasets the NewsFrames classifier was trained and evaluated on.
python -m pip install build twine
python -m build
python -m twine upload dist/*
rm -rf dist/*