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.
npm install --save sentiment-alyze
var sA =string = 'This string is super awesome! I feel like running and shopping'sentimentScore = sAtermFrequency = sAtermFrequencyNoStopWords = sAtermFrequencyPorterized = sAphrases ='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;console;console;
Fork, clone, lint, test, pull :-)