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NLP_final_project Texts

https://github.com/DigiUGA/Gutenberg_Text

#Helpful Resources:Coding Systems for Themes of Agency and Communion https://www.sesp.northwestern.edu/foley/instruments/agency/

#Article about word2vec digital humanities: https://www.reddit.com/r/MachineLearning/comments/4m7h4f/word_vectors_word2vec_in_eighteenthcentury/ http://bookworm.benschmidt.org/posts/2015-10-25-Word-Embeddings.html http://ryanheuser.org/word-vectors-1/ http://ryanheuser.org/word-vectors-2/

Word2Vec: https://colab.research.google.com/drive/1rJJifX_aL63JNqAnTOXPnXm078ejC-1n

List of autobiographies/letters in Project Gutenburg: Anderson, Hans Christian - The True Story of my Life (1847) Austin, Jane - The Letters of Jane Austen (1884) Balzac, Honore - Letters to Madam Hanska (1833) Conrad, Joseph - Notes on My Life & Letters (1898-1919) Dumas, Alexandre - My Memoirs Vol 2 - Vol 6 (1844-1846) Franklin, Benjamin - Autobiography and Memoirs (1791) Gibbon, Edward - Private Letters of Edward Gibbon (1753-1794) Goethe, Johann Wolgang von - The Autobiography of Goethe (1774) Letters from Switzerland and Travels in Italy Hugo, Victor - The Memoirs of Victor Hugo (1899) James, Henry - The Letters of Henry James (1892-1911) Morley, Henry - Letters to Sir William Windham and Mr. Pope (1717) Stevenson, Robert Louis - Memories and Portraits (1887) Thorough, Henry David -- journal entries (1837-1854) Trollope, Anthony - An Autobiography of Anthony Trollope (1876) Twain, Mark — autobiography and letters (1835-1910) Voltaire — autobiography and letters (1745)

#numbers cat -n voltaire_letters.txt | grep LETTER

#gets text cat voltaire_letters.txt | awk "129 <= NR && NR <= 3738" > voltaire_letters_headings.txt

1.) Setup Tool/ENV/Setup

Python 3.7.3 MacOS High Sierra conda install numpy conda install spacy conda install requests #This will be a siginificant amount of memory 0.6 gb conda install -c conda -forge spacy-model-en_core_web_lg

3.) #gathering synonyms python agency_synonyms.py python communion_synonyms.py

4.) Michael Joseph Hearn

5.) The project was done with a combination of scripts working in an ordered fashion. Collect documents Recieved Words thematicly related to agency and communion web scraped synonyms Load spacy word embeddings Collect words from docs Compare similarity between synonyms and words common to docs Use matplotlib to plot scores

https://colab.research.google.com/drive/1rJJifX_aL63JNqAnTOXPnXm078ejC-1n

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NLP datasci2 final project. Agency vs Communion

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