Analysis of tweets text. Gives the sentiment analysis of all the tweets. The data file is included. Used NLTK and Python 3.
• Loding the data • Processing and cleaning the data using punctuation, NLTK Stop words etc. Removing all the hashtags, alphatags, special symbols etc. • Getting the most frequest hashtags from the tweets. • Plotting the most frequest words used in tweets. • Computing the Sentiment Analysis of all the tweets.
I used NLTK to compute the Sentiment Analysis but it can also be done using the TextBlob library (python)
Code for textblob function is given below:
from textblob import TextBlob
def textblob_sentiment(arg1): #arg1 can be any reviews, tweets and similar. Make sure to clean the data first. sentiment_textblob = TextBlob(reviews) return(sentiment_textblob.sentiment.polarity)