b671ff51f9
Normalize polarity values in sentiment-basic and sentiment-140 |
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.. | ||
emotion-wnaffect.py | ||
emotion-wnaffect.senpy | ||
emotion.py | ||
README.md | ||
test_wna.py | ||
wnaffect.py |
WordNet-Affect plugin
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:
- anger : general-dislike
- fear : negative-fear
- disgust : shame
- joy : gratitude, affective, enthusiasm, love, joy, liking
- sadness : ingrattitude, daze, humlity, compassion, despair, anxiety, sadness
Usage
The parameters accepted are:
- Language: English (en).
- Input: Text to analyse.
Example request:
http://senpy.cluster.gsi.dit.upm.es/api/?algo=emotion-wnaffect&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.
The response of this plugin uses Onyx ontology developed at GSI UPM for semantic web.
This plugin uses WNAffect labels for emotion analysis.
The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
Known issues
- This plugin uses the pattern library, which means it will only run on python 2.7
- 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.
- You can download Wordnet 1.6 here: http://wordnetcode.princeton.edu/1.6/wn16.unix.tar.gz and extract the dict folder.
- The hierarchy and synsets files can be found here: https://github.com/larsmans/wordnet-domains-sentiwords/tree/master/wn-domains/wn-affect-1.1
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