Pros and Cons of NLTK Sentiment Analysis with VADER

Jayson DeLancey

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29 May 2020CPOL3 min read

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This article is the fourth in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this and additional articles, we’re going to try and improve upon our approach to analyzing the sentiment of our communities.

We’ll recap how NLTK and Python can be used to quickly get a sentiment analysis of posts from Reddit using VADER, and the trade-offs of this approach.

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This article is part of the series 'Sentiment Analysis ◁ Prev View All Next ▷

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

Written By

Jayson DeLancey

Technical Lead

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).

Pros and Cons of NLTK Sentiment Analysis with VADER

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