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Object-oriented software implemented in Python based on Machine Learning and SpaCy. --- Python project based on The persuasiveness metric is concluded from a systematic literature review on persuasive natural language processing. It quantitatively determines the persuasiveness of any given email and compares it to 20.000 other successful emails.

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Determining the Persuasiveness of an Arbitrary Email

This repository introduces the persuasiveness metric.

  • The persuasiveness metric is concluded from a systematic literature review on persuasive natural language processing. It quantitatively determines the persuasiveness of any given email.
  • This persuasiveness metric scores a message through a comparison to 20.000 successful messages. These were extracted, scored and compiled from the (GMANE) email dataset. It consists of 160 million emails.
  • Additionally, this persuasvieness-metric provides a word level analysis of the text, and gives descriptive indices of the input email. These indices are inspired by the Text Complexity Analyzer implementation by Hans.
  • This object oriented project is based on SpaCy v3, and can be deployed as a FastAPI microservice on Google Cloud Run.

Please contact me in case you need any information or have any questions.

Instructions to run the persuasiveness metric locally:

git clone https://github.com/seduerr91/persuasiveness-metric
cd persuasiveness-metric
pip3 install -r requirements.txt
python3 app.py

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Object-oriented software implemented in Python based on Machine Learning and SpaCy. --- Python project based on The persuasiveness metric is concluded from a systematic literature review on persuasive natural language processing. It quantitatively determines the persuasiveness of any given email and compares it to 20.000 other successful emails.

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