wp-senpy
This plugin analyses the emotions and sentiments expressed by users on comments using Senpy.
Plugin info
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Possibly abandoned • Last updated 3046 days ago
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Possibly abandoned (last update 3046 days ago).
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Description
This plugin analyses the emotions and sentiments expressed by user on comments. It uses Senpy as a service for using several sentiment or emotion analysis algorithms. Senpy is an open source framework to build semantic and emotion analysis services that has been developed by the GSI of ETSIT-UPM.It returns data using semantic vocabularies such as Marl or Onyx.
The user will be able to select between the different emotions and sentiment algorithms available. This plugin uses the [Senpy API] (http://senpy.readthedocs.io/en/latest/apischema.html) for analysing the sentiments and emotions on comments.
Moreover, this analysis will be stored in the database. The user will select whether he wants to show this analysis information on comments or not.
For more information about Senpy and its available plugins, please visit http://test.senpy.cluster.gsi.dit.upm.es/#about
Installation
- Upload the plugin files to the
/wp-content/plugins/wp-senpydirectory, or install the plugin through the WordPress plugins screen directly. - Activate the plugin through the ‘Plugins’ screen in WordPress
- Use the Emotion & Sentiment Menu screen to configure the plugin and Senpy parameters.
- Use the Emotion & Sentiment Menu > Comments Layout for selecting what to show in the comment’s view
Frequently Asked Questions
Installation Instructions
- Upload the plugin files to the
/wp-content/plugins/wp-senpydirectory, or install the plugin through the WordPress plugins screen directly. - Activate the plugin through the ‘Plugins’ screen in WordPress
- Use the Emotion & Sentiment Menu screen to configure the plugin and Senpy parameters.
- Use the Emotion & Sentiment Menu > Comments Layout for selecting what to show in the comment’s view
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Screenshots
Changelog
0.1
- Analyse comments using Senpy framework Service API.
- Basic configuration of comments visualization.