【520】利用 TextBlob & Vader 进行情感分析

参考：Tutorial: Quickstart - TextBlob （sentiment analysis）

参考：An overview of sentiment analysis python library: TextBlob

参考：How does TextBlob calculate sentiment polarity? How can I calculate a value for sentiment with machine learning classifier?

参考：Sentiment Analysis: VADER or TextBlob?

1. Installation of TextBlob

　　Installation is not a big deal here. If you are already using CMD, you have to run this command to install TextBlob. Go to CMD and enter:

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1	pip install textblob

　　You need to download corpus first to train the model of TextBlob. You can achieve it using the following command:

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1	python -m textblob.download_corpora

 

2. Steps for Sentiment Analysis Python using TextBlob

　　Here is a sample code of how I used TextBlob in tweets sentiments:

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from textblob import TextBlob ### My input text is a column from a dataframe that contains tweets.   def sentiment(x):     sentiment = TextBlob(x)     return sentiment.sentiment.polarity   tweetsdf['sentiment'] = tweetsdf['processed_tweets'].apply(sentiment) tweetsdf['senti'][tweetsdf['sentiment']>0] = 'positive' tweetsdf['senti'][tweetsdf['sentiment']<0] = 'negative' tweetsdf['senti'][tweetsdf['sentiment']==0] = 'neutral'

　　another example:

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>>> from textblob import TextBlob >>> testimonial = TextBlob("My name is Alex") >>> testimonial.sentiment.polarity 0.0 >>> testimonial = TextBlob("I feel a little headache") >>> testimonial.sentiment.polarity -0.1875 >>> testimonial = TextBlob("I can't remember anything") >>> testimonial.sentiment.polarity 0.0 >>> testimonial = TextBlob("I feel so unhappy") >>> testimonial.sentiment.polarity -0.6 >>> testimonial = TextBlob("I really like this toy") >>> testimonial.sentiment.polarity 0.2 >>> testimonial = TextBlob("I really want this toy") >>> testimonial.sentiment.polarity 0.2 >>> testimonial = TextBlob("I really don't want this toy") >>> testimonial.sentiment.polarity 0.2 >>> testimonial = TextBlob("I really don't like this toy") >>> testimonial.sentiment.polarity 0.2 >>> testimonial = TextBlob("I really hate this toy") >>> testimonial.sentiment.polarity -0.8

 

3. Installation of Vader

　　Go to CMD and enter:

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1	pip install vaderSentiment

 

4. Steps for Sentiment Analysis Python using Vader

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>>> from nltk.sentiment.vader import SentimentIntensityAnalyzer >>> sid = SentimentIntensityAnalyzer() >>> sid.polarity_scores("I like this movie") {'neg': 0.0, 'neu': 0.444, 'pos': 0.556, 'compound': 0.3612} >>> sid.polarity_scores("My name is Alex") {'neg': 0.0, 'neu': 1.0, 'pos': 0.0, 'compound': 0.0} >>> sid.polarity_scores("My name is Alex and hate myself") {'neg': 0.381, 'neu': 0.619, 'pos': 0.0, 'compound': -0.5719}

• compound > 0, positive
• compound < 0, negative
• compound = 0, neutral

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>>> def sentiment_vader(x):     sentiment = SentimentIntensityAnalyzer()     return sentiment.polarity_scores(x)['compound']   >>> sentiment_vader('I like this movie') 0.3612 >>> sentiment_vader('I donot know what to do now') 0.0 >>> sentiment_vader('I will go to school very early tomorrow and feel a little terrible') -0.4228