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    sentiment-alyze

    2.0.0 • Public • Published

    Build Status

    sentiment-alyze

    Node package for conducting textual analysis. The sentimentalyze method takes a string as its argument and returns a sentiment score calculated using AFINN-111. The termFrequency method also takes a string as its argument and returns an object with the count of words in that string. Filtering out English stop-words is optional.

    Porter stemming algorithm reduces tokens to base, e.g. 'run', 'running', and 'runs' will all convert to 'run'.

    Values of words in AFINN-111 range between -5 and +5.

    Installation:

    npm install --save sentiment-alyze

    Usage:

    var sA = require('sentiment-alyze'),
        string = 'This string is super awesome! I feel like running and shopping',
        sentimentScore = sA.sentimentalyze(string),
        termFrequency  = sA.termFrequency(string),
        termFrequencyNoStopWords = sA.termFrequency(string, {stopWords: 'no'}),
        termFrequencyPorterized = sA.termFrequency(string, {stopWords: 'no', stem: 'yes'}),
        phrases = [
                   'Virgina Woolf wrote To the Lighthouse',
                   'Virginia Woolf was an English author who lived in London.',
                   'Virginia Woolf lived in London. London was important to her. '],
        tfIDF = sA.tfIDF(phrases);
     
     
        console.log('sentiment score ', sentimentScore, 'term frequency, all words ', termFrequency, 'term frequency, no stop words ', termFrequencyNoStopWords, 'porterized ', termFrequencyPorterized);
        console.log('term frequency-inverse document frequency ', tfIDF);
     

    Tests

    npm test;

    Contributing

    Fork, clone, lint, test, pull :-)

    Keywords

    none

    Install

    npm i sentiment-alyze

    DownloadsWeekly Downloads

    5

    Version

    2.0.0

    License

    The MIT License

    Unpacked Size

    67.4 kB

    Total Files

    17

    Last publish

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