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https://github.com/winkjs/wink-sentiment
Accurate and fast sentiment scoring of phrases with #hashtags, emoticons :) & emojis 🎉
https://github.com/winkjs/wink-sentiment
emoji emoticons hashtag nlp sentiment sentiment-analysis sentiment-classification sentiment-scores wink
Last synced: about 1 month ago
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Accurate and fast sentiment scoring of phrases with #hashtags, emoticons :) & emojis 🎉
- Host: GitHub
- URL: https://github.com/winkjs/wink-sentiment
- Owner: winkjs
- License: mit
- Created: 2017-11-02T06:23:50.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-02-27T17:26:32.000Z (almost 2 years ago)
- Last Synced: 2024-10-30T01:59:23.343Z (3 months ago)
- Topics: emoji, emoticons, hashtag, nlp, sentiment, sentiment-analysis, sentiment-classification, sentiment-scores, wink
- Language: JavaScript
- Homepage: http://winkjs.org/wink-sentiment
- Size: 1.62 MB
- Stars: 62
- Watchers: 6
- Forks: 13
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# wink-sentiment
Accurate & fast sentiment scoring of phrases with #hashtags, emoticons:) & emojis🎉
### [](https://travis-ci.org/winkjs/wink-sentiment) [](https://coveralls.io/github/winkjs/wink-sentiment?branch=master) [](https://david-dm.org/winkjs/wink-sentiment) [](https://david-dm.org/winkjs/wink-sentiment?type=dev) [](https://gitter.im/winkjs/Lobby)
[
](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.