Through this way, we can utilize this tweet data for other experimental purposes. Later all the processed data will be saved to a CSV file in the local system. Here, we will create a data frame of all the tweet data that we have downloaded. Sentiment Analysis #Sentiment Analysis Report #Finding sentiment analysis (+ve, -ve and neutral) pos = 0 neg = 0 neu = 0 for tweet in searched_tweets: analysis = TextBlob(tweet.text) if ntiment>0: pos = pos +1 elif ntiment<0: neg = neg + 1 else: neu = neu + 1 print("Total Positive = ", pos) print("Total Negative = ", neg) print("Total Neutral = ", neu) #Plotting sentiments labels = 'Positive', 'Negative', 'Neutral' sizes = colors = explode = (0.1, 0, 0) # explode 1st slice plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True, startangle=140) plt.axis('equal') plt.show() We will now analyze the sentiments of tweets that we have downloaded and then visualize them here. #Defining Search keyword and number of tweets and searching tweets query = 'lockdown' max_tweets = 2000 searched_tweets =
You can pass the keyword of your interest here and the maximum number of tweets to be downloaded through the tweepy API. #Authorization and Search tweets #Getting authorization consumer_key = 'XXXXXXXXXXXXXXX' consumer_key_secret = 'XXXXXXXXXXXXXXX' access_token = 'XXXXXXXXXXXXXXX' access_token_secret = 'XXXXXXXXXXXXXXX' auth = tweepy.OAuthHandler(consumer_key, consumer_key_secret) t_access_token(access_token, access_token_secret) api = tweepy.API(auth, wait_on_rate_limit=True) After you create the app, not down the below-required credentials from there. After creating the account, go to ‘Get Started’ option and navigate to the ‘Create an app’ option. To use the ‘ tweepy‘ API, you need to create an account with Twitter Developer. #Importing Libraries import tweepy from textblob import TextBlob import pandas as pd import numpy as np import matplotlib.pyplot as plt import re import nltk nltk.download('stopwords') from rpus import stopwords from import PorterStemmer from wordcloud import WordCloud import json from collections import Counter Downloading the data from Twitter
Make sure to install ‘tweepy’, ‘ textblob ‘ and ‘ wordcloud ‘ libraries using ‘ pip install tweepy ’, ‘ pip install textblob ‘ and ‘ pip install wordcloud ‘. We will import all the required libraries here. Here, we will discuss a hands-on approach to download and analyze twitter data.
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