merelinguist / mindreader

Super simple sentiment analysis with AFINN.

Home Page:https://npm.im/mindreader

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Super simple sentiment analysis with AFINN.

Usage

npm i styled-preflight
yarn add styled-preflight
import { mindreader } from 'mindreader';

const sentiment = mindreader('good, bad');

console.log(sentiment);

/*
{
  score: -3,
  comparative: -1,
  calculation: [{ ugly: -3 }, { bad: -3 }, { good: 3 }],
  tokens: ['good', 'bad', 'ugly'],
  words: ['ugly', 'bad', 'good],
  positive: ['good']
  negative: ['ugly', 'bad']
}
*/

Input & Ouput

Input

mindreader takes any string input, for example:

import { mindreader } from 'mindreader';

const sentiment = mindreader(
  'It was the best of times, it was the worst of times...'
);

...

Output

The full output looks like this:

Name Type Description
score number The overall sentiment score. Essentially just the sentiment ratings of each token, added up.
comparative number If you want to compare several strings, use this. It calculates the average score of all the tokens in your provided string.
calculation { [key: string]: number }[] How did we get here? This outputs the score which was assigned to each individual token in the string. If you want to do word-by-word sentiment analysis, passing in a big string to mindreader, and then reading from caluclation is the fastest way of doing it.
tokens string[] A list of the words in your string.
words string[] All the words which mindreader actually scanned. Some stopwords, like “the”, or rarer words will not be included here.
positive number A list of the positive marked words (those scored above 0) .
negative number A list of the positive marked words (those scored below 0) .

Prior art

About

Super simple sentiment analysis with AFINN.

https://npm.im/mindreader

License:MIT License


Languages

Language:TypeScript 100.0%