Created
March 3, 2014 15:19
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Analyze Twitter sentiment for your brand using Textalytics Media Analysis API
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import smaclient | |
from TwitterAPI import TwitterAPI | |
import matplotlib.pyplot as plt | |
# Go to http://dev.twitter.com and create an app. | |
# The consumer key and secret will be generated for you after | |
consumer_key = <consumer-key> | |
consumer_secret = <consumer-secret> | |
# After the step above, you will be redirected to your app's page. | |
# Create an access token under the the "Your access token" section | |
access_token_key = <access-token-key> | |
access_token_secret = <access-token-secret> | |
# Register in https://textalytics.com | |
# Log in and get a licence for Textalytics Media Analysis API | |
license_key = <textalytics-license-key> | |
# Create a Twitter client | |
twitter = TwitterAPI(consumer_key, consumer_secret, access_token_key, access_token_secret) | |
# Create a Textalytics client | |
textalytics = smaclient.SmaClient(license_key) | |
textalytics.fields = 'sentiment' | |
# Analyze sentiment for Nokia in Spanish, retrieve at most 100 tweets | |
brand = 'Nokia' | |
language = 'es' | |
max_tweets = 100 | |
labels = ['P', 'N', 'NEU', 'NONE'] | |
colors = ['yellowgreen','lightcoral','gold','lightskyblue'] | |
# Initialize sentiments to aggregate sentiment count | |
total = 0 | |
sentiments = {} | |
for label in labels: | |
sentiments[label] = 0 | |
# Search and analyze tweets | |
query = {'q' : brand, 'lang' : language, 'count': max_tweets} | |
results = twitter.request('search/tweets', query ) | |
for tweet in results.get_iterator(): | |
doc = smaclient.Document(tweet['id'], tweet['text']) | |
doc.language = language | |
doc.source = 'TWITTER' | |
response = textalytics.analyze(doc) | |
if (isinstance(response,smaclient.Response)): | |
print response.result.sentiment, ' ', tweet['text'] | |
sentiments[response.result.sentiment] = sentiments[response.result.sentiment] + 1 | |
total = total + 1 | |
# Plot a pie chart | |
sizes = [sentiments['P']/float(total), sentiments['N']/float(total), sentiments['NEU']/float(total), sentiments['NONE']/float(total)] | |
print sizes | |
plt.pie(sizes,labels=labels, colors=colors, autopct='%1.1f%%', shadow=True) | |
plt.title(brand + ' sentiment using Textalytics Media Analysis 1.0') | |
plt.axis('equal') | |
plt.show() |
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Hi zdepablo, I am facing error running your code.The error is with smaclient which is no more supported in python packages.Can you please help?