/Sentiment-Analysis-of-FIFA-WC-tweets

A random collection of 5.3 lac tweets on the FIFA world cup 2018 starting from the Round of 16 till the World Cup Final were analyzed using the TextBlob library which has a pre-trained built in lexicon to classify them as either positive, negative or neutral. A pie chart was used to show the percentage of positive, negative or neutral tweets related to the world cup.

Primary LanguagePython

Sentiment-Analyzer-Twitter

A random collection of 5.3 lac tweets on the FIFA world cup 2018 starting from the Round of 16 till the World Cup Final were analyzed using the Naive Bayes classifier to classify them as either positive, negative or neutral. A pie chart was used to show the percentage of positive, negative or neutral tweets related to the world cup.

#Note: Please extract the FIFA.zip file in the same directory and then run the python program.