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senpy/community-plugins/sentiment-vader
J. Fernando Sánchez e1d888ebd6 Add 'community-plugins/' from commit '4c73797246c6aff8d055abfef73d3f0d34b933a8'
git-subtree-dir: community-plugins
git-subtree-mainline: 7f712952be
git-subtree-split: 4c73797246
2023-09-20 13:32:30 +02:00
..
README.md Add 'community-plugins/' from commit '4c73797246c6aff8d055abfef73d3f0d34b933a8' 2023-09-20 13:32:30 +02:00
vader_plugin.py Add 'community-plugins/' from commit '4c73797246c6aff8d055abfef73d3f0d34b933a8' 2023-09-20 13:32:30 +02:00
vader_sentiment_lexicon.txt Add 'community-plugins/' from commit '4c73797246c6aff8d055abfef73d3f0d34b933a8' 2023-09-20 13:32:30 +02:00
vaderSentiment.py Add 'community-plugins/' from commit '4c73797246c6aff8d055abfef73d3f0d34b933a8' 2023-09-20 13:32:30 +02:00

Sentimet-vader plugin

Vader is a plugin developed at GSI UPM for sentiment analysis.
The response of this plugin uses Marl ontology developed at GSI UPM for semantic web.

Acknowledgements

This plugin uses the vaderSentiment module underneath, which is described in the paper:

VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text C.J. Hutto and Eric Gilbert Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.

If you use this plugin in your research, please cite the above paper.

For more information about the functionality, check the official repository

https://github.com/cjhutto/vaderSentiment

Usage

Parameters:

  • Language: es (Spanish), en(English).
  • Input: Text to analyse.

Example request:

http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-vader&language=en&input=I%20love%20Madrid

Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit senpy documentation. Specifically, NIF API section.

This plugin supports python3

alt GSI Logo

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