Machine Learning Algorithms

VADER sentiment analysis with NLTK

For the English language, NLTK provides an already trained model called VADER (Valence Aware Dictionary and sEntiment Reasoner) that works in a slightly different way and adopts a rule engine together with a lexicon to infer the sentiment intensity of a piece of text. More information and details can be found in Hutto C.J., Gilbert E., VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text, AAAI, 2014.

The NLTK version uses the SentimentIntensityAnalyzer class and can immediately be used to have a polarity sentiment measure made up of four components:

• Positive factor
• Negative factor
• Neutral factor
• Compound factor

The first three don't need any explanation, while the last one ...