VADER
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a widely used sentiment analysis tool tailored for understanding emotions in text, especially in social media contexts. Developed by C.J. Hutto and Eric Gilbert, it combines lexicon-based methods with grammatical and syntactical rules, offering precise sentiment analysis. VADER excels at capturing sentiment intensity, polarity (positive, negative, neutral), and even nuances like sarcasm, thanks to empirically validated linguistic rules and datasets.
Originally presented at the Eighth International Conference on Weblogs and Social Media in 2014, VADER was designed for scalability and ease of use. Its open-source implementation in Python is accessible for various applications, from marketing analysis to social media monitoring. The tool incorporates features like emoticons, slang, and acronyms, making it uniquely adept at analyzing informal text. Users can install it via Python’s pip command, and the source code is freely available under the MIT License.
The tool has been validated rigorously with human raters to ensure accuracy. Datasets like tweets, movie reviews, and editorial snippets were used for its development, enabling a robust understanding of diverse text formats.
For official details, you can visit VADER’s documentation: VADER Sentiment.
Releated resources
- Medium post : A Short Introduction to VADER
- Paper: VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text. 2014
- DOI: 10.1609/icwsm.v8i1.14550
- Read on ojs.aaai.org
- Article: VADER sentiment analysis
- NLTK module: nltk.sentiment.vader module