text_blob_module [Neurosurgery Wiki]

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TextBlob is a Python (2 and 3) library for processing textual data. It provides a consistent API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and more. 

Sentiment analysis via Text Blob was done on both the “Results” and the “Conclusions” paragraphs, resulting in a numerical output for polarity and subjectivity
((TextBlob, Simplified Text Processing. https://textblob.
readthedocs.io/en/dev/. Accessed 4 April 2020.))
The generic Text Blob algorithm was used without changing the libraries of positive and negative key words.
For evaluation of machine learning to classify the abstracts according to their importance, Fischer and Steiger used [[Python]]’s [[Keras]]
library, built on [[Tensorflow]], and the word frequency based tokenizer
((Keras documentation. https://keras.io/. Accessed 4
April 2020.))