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https://github.com/gsi-upm/senpy
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50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
# -*- coding: utf-8 -*-
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from vaderSentiment import sentiment
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from senpy.plugins import SentimentPlugin, SenpyPlugin
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from senpy.models import Results, Sentiment, Entry
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import logging
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logger = logging.getLogger(__name__)
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class vaderSentimentPlugin(SentimentPlugin):
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def analyse_entry(self,entry,params):
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logger.debug("Analysing with params {}".format(params))
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text_input = entry.get("text", None)
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aggregate = params['aggregate']
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score = sentiment(text_input)
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opinion0 = Sentiment(id= "Opinion_positive",
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marl__hasPolarity= "marl:Positive",
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marl__algorithmConfidence= score['pos']
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)
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opinion1 = Sentiment(id= "Opinion_negative",
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marl__hasPolarity= "marl:Negative",
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marl__algorithmConfidence= score['neg']
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)
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opinion2 = Sentiment(id= "Opinion_neutral",
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marl__hasPolarity = "marl:Neutral",
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marl__algorithmConfidence = score['neu']
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)
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if aggregate == 'true':
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res = None
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confident = max(score['neg'],score['neu'],score['pos'])
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if opinion0.marl__algorithmConfidence == confident:
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res = opinion0
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elif opinion1.marl__algorithmConfidence == confident:
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res = opinion1
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elif opinion2.marl__algorithmConfidence == confident:
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res = opinion2
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entry.sentiments.append(res)
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else:
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entry.sentiments.append(opinion0)
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entry.sentiments.append(opinion1)
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entry.sentiments.append(opinion2)
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yield entry
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