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https://github.com/merelinguist/mindreader
Super simple sentiment analysis with AFINN.
https://github.com/merelinguist/mindreader
afinn nlp sentiment sentiment-analysis sentiment-scores tsdx typescript
Last synced: 24 days ago
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Super simple sentiment analysis with AFINN.
- Host: GitHub
- URL: https://github.com/merelinguist/mindreader
- Owner: merelinguist
- License: mit
- Created: 2020-03-26T21:35:01.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-01-05T17:21:28.000Z (almost 2 years ago)
- Last Synced: 2024-11-29T13:53:29.280Z (25 days ago)
- Topics: afinn, nlp, sentiment, sentiment-analysis, sentiment-scores, tsdx, typescript
- Language: TypeScript
- Homepage: https://npm.im/mindreader
- Size: 1.58 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 14
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Super simple sentiment analysis with AFINN.
## Usage
```sh
npm i styled-preflight
```
```sh
yarn add styled-preflight
```
```js
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:
```js
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
- https://github.com/thisandagain/sentiment