A practical example – Twitter real-time sentiment analysis

Twitter is said to have almost 7,000 tweets every second on a wide variety of topics. Let's try to build a sentiment analyzer that can capture the emotions of the news from different news sources in real time. We will start by importing the required packages:

1. Import the needed packages:

import tweepy,json,time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
analyzer = SentimentIntensityAnalyzer()

Note that we are using the following two packages:

2. VADER sentiment analysis, which stands for Valence Aware Dictionary and Sentiment Reasoner. It is one of the popular rule-based sentiment analysis tools that is developed for social media. If you have never used it before, then you will first have to run the following...