@happyaccident/wink-sentiment/README.md

Accurate and fast sentiment scoring of phrases with emoticons :) & emojis 🎉

# wink-sentiment

Accurate & fast sentiment scoring of phrases with #hashtags, emoticons:) & emojis🎉

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[<img align="right" src="https://decisively.github.io/wink-logos/logo-title.png" width="100px" >](http://winkjs.org/)

Analyze sentiment of tweets, product reviews, social media content or any text using **`wink-sentiment`**. It is based on [AFINN](https://arxiv.org/abs/1103.2903) and [Emoji Sentiment Ranking](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144296); it's features include:

1. Intelligent negation handling; for example, phrase "good product" will get a positive score whereas "not a good product" gets a negative score.
2. Automatic detection and scoring of two-word phrases in a text; for example, "cool stuff", "well done", and "short sighted".
3. Processes each emoji, emoticon and/or hashtag separately while scoring.
4. Embeds a powerful [tokenizer](https://www.npmjs.com/package/wink-tokenizer) that returns the tokenized phrase.
5. Returns the sentiment score and tokens. Each token contains a set of properties defining its sentiment, if any.
6. Achieves accuracy of 77%, when validated using Amazon Product Review [Sentiment Labelled Sentences Data Set](https://archive.ics.uci.edu/ml/machine-learning-databases/00331/) at [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/index.php).


### Installation

Use [npm](https://www.npmjs.com/package/wink-sentiment) to install:

    npm install wink-sentiment --save

### Getting Started
```javascript
// Load wink-sentiment package.
var sentiment = require( 'wink-sentiment' );
// Just give any phrase and checkout the sentiment score. A positive score
// means a positive sentiment, whereas a negative score indicates a negative
// sentiment. Neutral sentiment is signalled by a near zero score.

// Positive sentiment text.
sentiment( 'Excited to be part of the @imascientist team:-)!' );
// -> { score: 5,
//      normalizedScore: 2.5,
//      tokenizedPhrase: [
//        { value: 'Excited', tag: 'word', score: 3 },
//        { value: 'to', tag: 'word' },
//        { value: 'be', tag: 'word' },
//        { value: 'part', tag: 'word' },
//        { value: 'of', tag: 'word' },
//        { value: 'the', tag: 'word' },
//        { value: '@imascientist', tag: 'mention' },
//        { value: 'team', tag: 'word' },
//        { value: ':-)', tag: 'emoticon', score: 2 },
//        { value: '!', tag: 'punctuation' }
//      ]
//    }

// Negative sentiment text.
console.log( sentiment( 'Not a good product :(' ) );
// -> { score: -5,
//      normalizedScore: -2.5,
//      tokenizedPhrase: [
//        { value: 'Not', tag: 'word' },
//        { value: 'a', tag: 'word', negation: true },
//        { value: 'good', tag: 'word', negation: true, score: -3 },
//        { value: 'product', tag: 'word' },
//        { value: ':(', tag: 'emoticon', score: -2 }
//      ]
//    }

// Neutral sentiment text.
console.log( sentiment( 'I will meet you tomorrow.' ) );
// -> { score: 0,
//      normalizedScore: 0,
//      tokenizedPhrase: [
//        { value: 'I', tag: 'word' },
//        { value: 'will', tag: 'word' },
//        { value: 'meet', tag: 'word' },
//        { value: 'you', tag: 'word' },
//        { value: 'tomorrow', tag: 'word' },
//        { value: '.', tag: 'punctuation' }
//      ]
//    }
```
Try [experimenting with this example and more on Runkit](https://npm.runkit.com/wink-sentiment) in the browser.

### Documentation
Check out the [wink sentiment API](http://winkjs.org/wink-sentiment/) documentation to learn more.

### Need Help?

If you spot a bug and the same has not yet been reported, raise a new [issue](https://github.com/winkjs/wink-sentiment/issues) or consider fixing it and sending a pull request.

### About wink
[Wink](http://winkjs.org/) is a family of open source packages for **Statistical Analysis**, **Natural Language Processing** and **Machine Learning** in NodeJS. The code is **thoroughly documented** for easy human comprehension and has a **test coverage of ~100%** for reliability to build production grade solutions.

### Copyright & License

**wink-sentiment** is copyright 2017-18 [GRAYPE Systems Private Limited](http://graype.in/).

It is licensed under the terms of the MIT License.