/Sentiment-Analysis-of-tweets

Classification of tweets into positive and negative using classifiers like SVM, Logistic Regression, Naive bayes. Implementation of porter stemmer algorithm.

Primary LanguageJupyter Notebook

Sentiment Analysis Of Tweets

There are three folders

  • Document - Contains all the document part
  • Output - Contains graphs and final output data
  • src - Contains actual code of the project

Files that contain final code:

  • porter_stemmer.py
  • Naive_Bayes.ipynb
  • Logistic Regression.ipynb
  • NLTK.ipynb
  • SVM.ipynb
  • data_process_fb_amazon.ipynb
  • process_split_store.ipynb

Rest other file contains the code written during intermediate state and testing purpose.

By:-

  • Sopnesh Gandhi
  • Rushitkumar Jasani
  • Priyendu Mori
  • Niharika Khare