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Optimized text cleanup and function parameters

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This commit is contained in:
rnsrk 2023-01-13 20:26:04 +01:00
parent a20f7331bb
commit c6b16b9ccf
3 changed files with 21 additions and 21 deletions
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10
SentiTooter.py
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@ -28,14 +28,14 @@ class SentiTooter:
self.labels = ['negative', 'neutral', 'positive']
self.sia = SentimentIntensityAnalyzer()
def analyze(self, toot):
match toot.language:
def analyze(self, language, content):
match language:
case 'de':
sentiment = self.deModel.predict_sentiment([toot.content])
sentiment = self.deModel.predict_sentiment([content])
sentiment.append('germanSentiment')
return sentiment
case 'en':
text = preprocess(toot.content)
text = preprocess(content)
encoded_input = self.enTokenizer(text, return_tensors='pt')
output = self.enModel(**encoded_input)
scores = output[0][0].detach().numpy()
@ -45,7 +45,7 @@ class SentiTooter:
sentiment = [sentimentLabel, 'twitter-roberta-base-sentiment']
return sentiment
case _:
compound = self.sia.polarity_scores(toot.content)['compound']
compound = self.sia.polarity_scores(content)['compound']
if compound > (1 / 3):
return ['positive', 'vaderSentiment']
elif compound < (-1 / 3):