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Uses streaming twitter data based on custom keyword to generate the sentiment of users around that keyword using TextBlob.

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Twitter Sentiment Analysis using TextBlob

Meghna Chakraborty

[BTech 2nd Year - May 2020]

First program to try my hands in Natural Language Processing and visualising data. Implemented sentiment-analysis library to find out the stance of people on a particular topic.

Features

  • ✨ Written in Python to explore python libraries ✨
  • Took real time tweets from twitter by using tweepy API
  • Input given to API was the topic_keyword and number_of_tweets required
  • Used TextBlob python library for sentiment analysis on the tweets into 3 categories
  • 3 categories : Positive , Neutral , Negative
  • Used Matplotlib to display result as a graph

Installation

Requires Python 3 to run from command line

Go to to the below link and generate 4 auth parameters that are required to access twitter real-time data using tweepy

https://developer.twitter.com/en/docs/twitter-api/getting-started/getting-access-to-the-twitter-api

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Uses streaming twitter data based on custom keyword to generate the sentiment of users around that keyword using TextBlob.

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