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ml-sentiment
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Readme
Simple text sentiment analyser.
npm install ml-sentiment
var ml = require('ml-sentiment')
ml.classify('Rainy day but still in a good mood')
//=> 2 ... (overall positive sentiment)
Returns a positive number for positive sentiment association and negative number for negative sentiment association.
var longSentence = `Transform json to csv data. The difference to my other
module json2csv is json2csv-stream uses streams for transforming the incoming
data. The module is built with the new streaming API from Node.js v0.10.0 but
maintains backwards compatibility to earlier Node.js versions. Listen for
header and line events or pipe the data directly to a readable stream.`
var ml = require('ml-sentiment')()
ml.classify(longSentence)
//=> 0 ... (very boring encyclopedia like text)
ml.classify('Rainy day but still in a good mood')
//=> 2 ... (overall positive sentiment)
var ml = require('ml-sentiment')()
ml.classify(`not awesome`)
//=> -3 (negative)
ml.classify(`awesome`)
//=> 3 (positive)
var ml = require('ml-sentiment')({lang: 'de'})
ml.classify(`Es ist nicht so toll`)
//=> (negative)
Original model and data: Finn Årup Nielsen, "A new ANEW: Evaluation of a word list for sentiment analysis in microblogs", http://arxiv.org/abs/1103.2903
For german model: R. Remus, U. Quasthoff & G. Heyer: SentiWS - a Publicly Available German-language Resource for Sentiment Analysis. In: Proceedings of the 7th International Language Ressources and Evaluation (LREC'10), 2010
FAQs
Machine learner sentiment classifier, with ability to negate words, with english and german
The npm package ml-sentiment receives a total of 60 weekly downloads. As such, ml-sentiment popularity was classified as not popular.
We found that ml-sentiment demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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