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license PyPI version PyPI pyversions PyPI status


All you need to understand Twitter is tweetnlp!

Get Started

pip install tweetnlp


  • Named Entity Recognition
import tweetnlp 
model = tweetnlp.load('ner')  # Or `model = tweetnlp.NER()` 
model.ner('Jacob Collier is a Grammy-awarded English artist from London.')  # Or `model.predict`
>>> {
    'prediction': ['B-person', 'I-person', 'O', 'O', 'O', 'O', 'O', 'O', 'B-location'],
    'probability': [0.9606876969337463, 0.9834017753601074, 0.9816871285438538, 0.9896021485328674, 0.44137904047966003, 0.375810831785202, 0.8757674694061279, 0.9786785244941711, 0.9398059248924255],
    'input': ['Jacob', 'Collier', 'is', 'a', 'Grammy-awarded', 'English', 'artist', 'from', 'London.'],
    'entity_prediction': [
        {'type': 'person', 'entity': ['Jacob', 'Collier'], 'position': [0, 1], 'probability': [0.9606876969337463, 0.9834017753601074]},
        {'type': 'location', 'entity': ['London.'], 'position': [8], 'probability': [0.9398059248924255]}]
  • Sentiment Analysis
import tweetnlp 
model = tweetnlp.load('sentiment')  # Or `model = tweetnlp.Sentiment()` 
model.sentiment("How many more days until opening day? 😩")  # Or `model.predict`
  • Irony Detection
import tweetnlp 
model = tweetnlp.load('irony')  # Or `model = tweetnlp.Irony()` 
model.irony('If you wanna look like a badass, have drama on social media')  # Or `model.predict`
  • Hate Detection
import tweetnlp 
model = tweetnlp.load('hate')  # Or `model = tweetnlp.Hate()` 
model.hate('Whoever just unfollowed me you a bitch')  # Or `model.predict`
  • Offensive Detection
import tweetnlp 
model = tweetnlp.load('offensive')  # Or `model = tweetnlp.Offensive()` 
model.offensive("All two of them taste like ass. ")  # Or `model.predict`
  • Emoji Prediction
import tweetnlp 
model = tweetnlp.load('emoji')  # Or `model = tweetnlp.Emoji()` 
model.emoji('Beautiful sunset last night from the pontoon @ Tupper Lake, New York')  # Or `model.predict`
  • Emotion Analysis
import tweetnlp 
model = tweetnlp.load('emotion')  # Or `model = tweetnlp.Emotion()` 
model.emotion('I love swimming for the same reason I love meditating...the feeling of weightlessness.')  # Or `model.predict`

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