Our project is on Twitter Sentiment Analysis. Sentiment Analysis is the process of ‘computationally’ determining whether a piece of writing is positive, negative or neutral. It’s also known as opinion mining, deriving the opinion or attitude of a speaker.Our Project takes a keyword/hashtag and number of tweets ,to analyse from, as inputs and plots a pie chart for the same.
Technology used: Sentiment analysis combines natural language programming(NLP), text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. We have used Tweepy,TextBlob,Matplotlib,re,sys libraries.
Prerequisites:- Tweepy,TextBlob,Matplotlib
Installation: Tweepy: tweepy is the python client for the official Twitter API. Install it using following pip command: pip install tweepy
TextBlob: textblob is the python library for processing textual data. Install it using following pip command: pip install textblob
Matplotlib:matplotlib is the python library for plotting data. Install it using following pip command: pip install matplotlib
Project by:- Yash Agarwal(17dcs017) Kartik Goyal(17uec061) Sudhanshu Agrawal(17ucs161)