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Model Details

  • The SENTIMENTAL classifier trained to predict the likelihood that a comment will be perceived as positive or negative.
  • BERT based Text Classification.

Intended Use

  • Intended to be used for a wide range of use cases such as supporting human moderation and extracting polarity of review comments.
  • Not intended for fully automated moderation.
  • Not intended to make judgments about specific individuals.

Factors

  • Identity terms referencing frequently positive and negative emotions.

Metrics

• Accuracy, which measures the percentage of True Positive and True Negative.

Ethical Considerations

  • TODO

Quantitative Analyses

  • TODO

Training Data

  • TODO

Evaluation Data

  • TODO

Caveats and Recommendations

  • TODO
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