sentiment-custom-lists
v1.0.10
Published
AFINN-based sentiment analysis for Node.js. Prepared for different languages and context list
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sentiment custom lists - AFINN-based sentiment analysis for Node.js
This project is a fork of thisandagain/sentiment. This project do the same as the original project and add support to use other AFINN like lists to do sentiment analysis
Original description
Sentiment is a Node.js module that uses the AFINN-111 wordlist to perform sentiment analysis on arbitrary blocks of input text. Sentiment provides serveral things:
- Performance (see benchmarks below)
- The ability to append and overwrite word / value pairs from the AFINN wordlist
- A build process that makes updating sentiment to future versions of the AFINN word list trivial
Installation
npm install sentiment-custom-lists
Usage
var sentiment = require('sentiment-custom-lists');
var r1 = sentiment('Cats are stupid.');
console.dir(r1); // Score: -2, Comparative: -0.666
var r2 = sentiment('Cats are totally amazing!');
console.dir(r2); // Score: 4, Comparative: 1
Usage with another list
("de_de" list currently not existing)
var sentiment = require('sentiment-custom-lists');
var r1 = sentiment('Katzen sind dumm.', 'de_de');
console.dir(r1); // Score: -2, Comparative: -0.666
Adding / overwriting words
You can append and/or overwrite values from AFINN by simply injecting key/value pairs into a sentiment method call:
var sentiment = require('sentiment');
var result = sentiment('Cats are totally amazing!', 'en_us' {
'cats': 5,
'amazing': 2
});
console.dir(result); // Score: 7, Comparative: 1.75
Benchmarks
The primary motivation for designing sentiment
was performance. As such, it includes a benchmark script within the test directory that compares it against the Sentimental module which provides a nearly equivalent interface and approach. Based on these benchmarks, running on a MacBook Pro with Node 0.12.7, sentiment
is twice as fast as alternative implementations:
sentiment (Latest) x 544,714 ops/sec ±0.83% (99 runs sampled)
Sentimental (1.0.1) x 269,417 ops/sec ±1.06% (96 runs sampled)
To run the benchmarks yourself, simply:
make benchmark
Testing
npm test