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Twitter Data Sentiment Analysis

This repository was stored some code in ipynb files. The ipynb contain a code for classifying sentiment analysis for twiiter data.
The Feature extraction that are used in ipynb:

  1. TF-IDF Vectorizer
  2. Countvectorizer
  3. Hashing Vectorizer
  4. Bigram Vectorizer

The classifier that are used in ipynb:

  1. Logistic Regression
  2. Multinomial Naive Bayes

The pdf was a documentation of implementation sentiment analysis for twitter data using Spark with pyspark2.