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🦠| Sentiment analysis on tweets about covid-19 vaccinations using Soft-max Regression, FNN, RNN and BERT-Base-uncased.

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Sitaras/Twitter-Covid-Vaccination-Data-Sentiment-Analysis

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The purpose of this project is to do a sentiment analysis on tweets about Covid-19 vaccinations in 3 classes (0-neutral, 1-negative, 2-positive).To-do this, I experimented with 4 different types of models:

  1. Softmax Regression.
  2. Feed-Forward neural network.
  3. Bidirectional RNN neural network with LSTM & GRU cells (witout and with attention layer).
  4. BERT-Base-uncased.
ModelPrecisionRecallF1 ScoreAccuracy
Softmax Regression71 %71 %71 %71.12 %
Feed-Forward neural network58 %66 %61 %65.6 %
LSTM neural network70 %66 %67 %65.55 %
LSTM with attention layer69 %72 %70 %69.36 %
BERT-Base-uncased78 %71 %73 %71 %

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🦠| Sentiment analysis on tweets about covid-19 vaccinations using Soft-max Regression, FNN, RNN and BERT-Base-uncased.

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