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  • 【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:

    pip install textblob

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

    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:

    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:

    >>> 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:

    pip install vaderSentiment

    4. Steps for Sentiment Analysis Python using Vader

    >>> 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
    >>> 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

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  • 原文地址:https://www.cnblogs.com/alex-bn-lee/p/14257912.html
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