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Various text analysis applied on science-related texts in the COCA corpus

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.ipynb_checkpoints
.ipynb_checkpoints
 
 
__pycache__
__pycache__
 
 
Data Pre-processing - Academic section.ipynb
Data Pre-processing - Academic section.ipynb
 
 
Data Pre-processing - Magazine section.ipynb
Data Pre-processing - Magazine section.ipynb
 
 
Data Pre-processing - Newspaper section.ipynb
Data Pre-processing - Newspaper section.ipynb
 
 
Doc2Vec.ipynb
Doc2Vec.ipynb
 
 
Filtering science-related texts from docs.ipynb
Filtering science-related texts from docs.ipynb
 
 
Preprocess & Parse.ipynb
Preprocess & Parse.ipynb
 
 
README.md
README.md
 
 
T-SNE clustering.ipynb
T-SNE clustering.ipynb
 
 
TF-IDF.ipynb
TF-IDF.ipynb
 
 
Word Vector Clustering (DBSCAN).ipynb
Word Vector Clustering (DBSCAN).ipynb
 
 
Word Vector Clustering (K-Means).ipynb
Word Vector Clustering (K-Means).ipynb
 
 
Word Vector Clustering (Ward).ipynb
Word Vector Clustering (Ward).ipynb
 
 
Word2Vec(NOUNS only).ipynb
Word2Vec(NOUNS only).ipynb
 
 
Word2Vec.ipynb
Word2Vec.ipynb
 
 
news_sci_text_excel.pkl
news_sci_text_excel.pkl
 
 
preprocess_and_parse.py
preprocess_and_parse.py
 
 
wordcloud_function
wordcloud_function
 
 
wordcloud_function.py
wordcloud_function.py
 
 

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Corpus-Clustering-Project

Various text analysis applied on science-related texts in the COCA corpus

This project is aimed at analyzing science-related texts in the COCA corpus (Corpus of Contemporary American English). Currently, the magazine, academic, news sections in the corpus are used.
The data pipeline can be briefly described as follows:

  1. Preprocesisng
  • sort text ids that are related to science
  • done by sorting excel sheet containing text id numbers and specifications

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Various text analysis applied on science-related texts in the COCA corpus

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