mirror of https://github.com/gsi-upm/senpy
Added some documentation and changes to .senpy files.
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# WordNet-Affect plugin
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This plugin uses WordNet-Affect (http://wndomains.fbk.eu/wnaffect.html) to calculate the percentage of each emotion. The plugin classifies among five diferent emotions: anger, fear, disgust, joy and sadness. It is has been used a emotion mapping enlarge the emotions:
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- anger : general-dislike
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- fear : negative-fear
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- disgust : shame
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- joy : gratitude, affective, enthusiasm, love, joy, liking
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- sadness : ingrattitude, daze, humlity, compassion, despair, anxiety, sadness
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## Usage
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The parameters accepted are:
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- Language: English (en).
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- Input: Text to analyse.
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Example request:
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```
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http://senpy.cluster.gsi.dit.upm.es/api/?algo=emotion-wnaffect&language=en&input=I%20love%20Madrid
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```
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Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section.
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The response of this plugin uses [Onyx ontology](https://www.gsi.dit.upm.es/ontologies/onyx/) developed at GSI UPM for semantic web.
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This plugin uses WNAffect labels for emotion analysis.
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The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
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## Known issues
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- This plugin uses the pattern library, which means it will only run on python 2.7
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- Wnaffect and corpora files are not included in the repository, but can be easily added either to the docker image (using a volume) or in a new docker image.
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![alt GSI Logo][logoGSI]
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[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
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This plugin uses WNAffect labels for emotion analysis.
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The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
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Known issues
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============
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* This plugin uses the pattern library, which means it will only run on python 2.7
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* Wnaffect and corpora files are not included in the repository, but can be easily added either to the docker image (using a volume) or in a new docker image.
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