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Using Pre-trained VADER Models for NLTK Sentiment Analysis

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29 May 2020CPOL4 min read
This article is the third in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article, we'll look at techniques you can use to start doing the actual NLP analysis.
NLTK includes pre-trained models in addition to its text corpus. The VADER Sentiment Lexicon model, aimed at sentiment analysis on social media. Let's see how it works.




This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


About the Author

Jayson DeLancey
Technical Lead
United States United States
Jayson manages Developer Relations for Dolby Laboratories, helping developers deliver spectacular experiences with media.

Jayson likes learning and teaching about new technologies with a wide range applications and industries. He's built solutions with companies including DreamWorks Animation (Kung Fu Panda, How to Train Your Dragon, etc.), General Electric (Predix Industrial IoT), The MathWorks (MATLAB), Rackspace (Cloud), and HERE Technologies (Maps, Automotive).

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