https://github.com/ssciwr/moralization-analyzer

Automated identification of text structures related to moralization.
https://github.com/ssciwr/moralization-analyzer

Last synced: 6 months ago
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Automated identification of text structures related to moralization.

• Host: GitHub
• URL: https://github.com/ssciwr/moralization-analyzer
• Owner: ssciwr
• License: mit
• Created: 2022-07-18T12:53:12.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2025-04-09T21:09:07.000Z (6 months ago)
• Last Synced: 2025-04-09T21:35:48.152Z (6 months ago)
• Language: Python
• Homepage: https://ssciwr.github.io/moralization-analyzer
• Size: 87.1 MB
• Stars: 2
• Watchers: 2
• Forks: 3
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Automated recognition of moralization in written text

![License: MIT](https://img.shields.io/github/license/ssciwr/moralization)

![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/ssciwr/moralization/ci.yml?branch=main)

![codecov](https://img.shields.io/codecov/c/github/ssciwr/moralization)

![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=ssciwr_moralization&metric=alert_status)

![Language](https://img.shields.io/github/languages/top/ssciwr/moralization)

Automated identification of text structures related to moralization.

**_This project is currently under development!_**

## Installation

```

pip install git+https://github.com/ssciwr/moralization.git

```

## Example notebooks

Here you can find a few short introduction notebooks on google colab.

- [DemoNotebook_interactive_plots](https://colab.research.google.com/github/ssciwr/moralization/blob/main/notebooks/DemoNotebook_interactive_plots.ipynb)

- [DemoNotebook_spacy_model](https://colab.research.google.com/github/ssciwr/moralization/blob/main/notebooks/DemoNotebook_spacy_model.ipynb)

- [DemoNotebook_transformers_model](https://colab.research.google.com/github/ssciwr/moralization/blob/main/notebooks/DemoNotebook_transformers_model.ipynb)

Based on an annotated corpus, the automatic classification of moralization constructs in written text will be investigated.

The ability to identify different categories will be investigated:

1. Moral values

1. Acting entities

1. Communicative role

1. Consequence

The developed software will work with annotations from [INCEpTION](https://inception-project.github.io/).