如何使用 Google Cloud NL api 进行情绪分析?
How can I use Google Cloud NL api for sentiment analysis?
如何使用 Google cloud NL api 对来自 Twitter 的带有我选择的主题(关键字)的推文进行情绪分析?
我可以使用 Twitter(Twitter api)编写 python 脚本,了解人们对我使用 python 的 NL 库“TextBlob”选择的主题的感受
import tweepy from textblob import TextBlob
# Step 1 - Authenticate
consumer_key= 'CONSUMER_KEY_HERE'
consumer_secret= 'CONSUMER_SECRET_HERE'
access_token='ACCESS_TOKEN_HERE'
access_token_secret='ACCESS_TOKEN_SECRET_HERE'
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
#Step 3 - Retrieve Tweets
public_tweets = api.search('Trump')
#CHALLENGE - Instead of printing out each tweet, save each Tweet to a CSV file
#and label each one as either 'positive' or 'negative', depending on the sentiment
#You can decide the sentiment polarity threshold yourself
for tweet in public_tweets:
print(tweet.text)
#Step 4 Perform Sentiment Analysis on Tweets
analysis = TextBlob(tweet.text)
print(analysis.sentiment)
print("")
您可以使用 google-cloud
python module:
# Import the module and create a language client
from google.cloud import language
language_client = language.Client()
# Analyze the sentiment
document = language_client.document_from_html(tweet.text)
annotations = document.analyze_sentiment()
print(annotations.score, annotations.magnitude)
此外,您可以使用 tweepy Streaming API 中的 track
参数实时过滤特定主题的推文。
如何使用 Google cloud NL api 对来自 Twitter 的带有我选择的主题(关键字)的推文进行情绪分析?
我可以使用 Twitter(Twitter api)编写 python 脚本,了解人们对我使用 python 的 NL 库“TextBlob”选择的主题的感受
import tweepy from textblob import TextBlob
# Step 1 - Authenticate
consumer_key= 'CONSUMER_KEY_HERE'
consumer_secret= 'CONSUMER_SECRET_HERE'
access_token='ACCESS_TOKEN_HERE'
access_token_secret='ACCESS_TOKEN_SECRET_HERE'
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
#Step 3 - Retrieve Tweets
public_tweets = api.search('Trump')
#CHALLENGE - Instead of printing out each tweet, save each Tweet to a CSV file
#and label each one as either 'positive' or 'negative', depending on the sentiment
#You can decide the sentiment polarity threshold yourself
for tweet in public_tweets:
print(tweet.text)
#Step 4 Perform Sentiment Analysis on Tweets
analysis = TextBlob(tweet.text)
print(analysis.sentiment)
print("")
您可以使用 google-cloud
python module:
# Import the module and create a language client
from google.cloud import language
language_client = language.Client()
# Analyze the sentiment
document = language_client.document_from_html(tweet.text)
annotations = document.analyze_sentiment()
print(annotations.score, annotations.magnitude)
此外,您可以使用 tweepy Streaming API 中的 track
参数实时过滤特定主题的推文。