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Sentiment Analysis using facebook's popular "fasttext" library

The data set used here is a collection of 40,000 tweets tagged with 13 different sentiments which I got from Kaggle. The brief data summary are as:

  neutral       8638
  worry         8459
  happiness     5209
  sadness       5165
  love          3842
  surprise      2187
  fun           1776
  relief        1526
  hate          1323
  empty          827
  enthusiasm     759
  boredom        179
  anger          110

The attached notebook file reads the data from the .csv file, apply some preprocessing, perform training and testing and finally predicts the sentiment if an appropriate input in the form of a sentence(s) is provided to the classifier.

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