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This project seeks to use various NLP, Machine Learning, Visualizations and other Data Science Techniques to investigate early Christian texts generated from 0AD to approximately 200AD

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michaeltatarjr/NLP_Church_Fathers_Project

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Investigating the Influence of Ancient Texts on Early Christian Church Fathers

Executive Summary

This project aims to explore the correlation and connections between the writings of the Early Christian Church Fathers and ancient Near Eastern antiquity and source texts. Using Natural Language Processing (NLP), various text visualizations, text analysis, NLTK libraries, and other techniques, we will investigate how the writings of the Church Fathers up to 200 AD are influenced by different texts. Specifically, we will analyze which Church Fathers are influenced by the Old Testament, which by the New Testament, and their overall text similarity to each other.

Motivation

The goal of this project is to align timeless wisdom with real-world, innovative methodology. The intersection of ancient texts and modern data science techniques presents a unique and untested opportunity. The fascination with ancient, dusty writings from different eras and cultures drives this investigation, which leverages data science and NLP to analyze a rich historical corpus.

Data Questions

Our analysis will focus on the following questions:

  • What attributes does the complete corpus possess?
  • Are there any textual oddities within the corpus?
  • Which testament (Old or New) is most frequently referenced?
  • Which key passages are most cited?
  • How do specific passages, such as the Sermon on the Mount, and particular books influence the writers?
  • Can we map the authors geographically, theologically, or through other dimensions over time?

Minimum Viable Product (MVP)

To demonstrate the results of our analysis, the MVP will include:

  • A PowerPoint presentation summarizing the findings.
  • A detailed presentation of results.
  • An interactive Streamlit or R Dashboard featuring visualizations and insights.

About

This project seeks to use various NLP, Machine Learning, Visualizations and other Data Science Techniques to investigate early Christian texts generated from 0AD to approximately 200AD

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