Metadata-Version: 2.1
Name: vader-multi
Version: 3.2.2
Summary: VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.
Home-page: https://github.com/brunneis/vader-multi
Author: C.J. Hutto
Author-email: cjhutto@gatech.edu
License: MIT License: http://opensource.org/licenses/MIT
Download-URL: https://github.com/brunneis/vader-multi/archive/master.zip
Keywords: vader,sentiment,analysis,opinion,mining,nlp,text,data,text analysis,opinion analysis,sentiment analysis,text mining,twitter sentiment,opinion mining,social media,twitter,social,media
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Text Processing :: General
Description-Content-Type: text/markdown
Requires-Dist: requests

# VADER Sentiment Analysis Multilanguage
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media. It is fully open-sourced under the [MIT License] (we sincerely appreciate all attributions and readily accept most contributions, but please don't hold us liable).

> This version integrates the Google Translate API through the `translatte` Python library. It requires an active Internet connection in order to work.

## Installation
```bash
pip install vader-multi
```

### `class vaderSentiment.SentimentIntensityAnalyzer`
#### `polarity_scores(text)`
Returns a dictionary with the following keys: `{'neg': float, 'neu': float, 'pos': float, 'compound': float}`

```python
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

analyzer = SentimentIntensityAnalyzer()
analyzer.polarity_scores("VADER is smart, handsome, and funny.")
```

## Examples
```python
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

analyzer = SentimentIntensityAnalyzer()
analyzer.polarity_scores("VADER is smart, handsome, and funny.")
```

