Graphing Live Twitter Sentiment Analysis with NLTK with NLTK

Now that we have live data coming in from the Twitter streaming API, why not also have a live graph that shows the sentiment trend? To do this, we're going to combine this tutorial with the live matplotlib graphing tutorial.

If you want to know more about how the code works, see that tutorial. Otherwise:

import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib import style
import time

style.use("ggplot")

fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)

def animate(i):
    pullData = open("twitter-out.txt","r").read()
    lines = pullData.split('\n')

    xar = []
    yar = []

    x = 0
    y = 0

    for l in lines[-200:]:
        x += 1
        if "pos" in l:
            y += 1
        elif "neg" in l:
            y -= 1

        xar.append(x)
        yar.append(y)
        
    ax1.clear()
    ax1.plot(xar,yar)
ani = animation.FuncAnimation(fig, animate, interval=1000)
plt.show()

The next tutorial: Named Entity Recognition with Stanford NER Tagger