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README.md
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co2_eq_emissions: 2.0686690092905224
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---
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# Model Trained Using AutoNLP
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- Problem type: Binary Classification
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co2_eq_emissions: 2.0686690092905224
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# Description
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This model takes a tweet with the word "jew" in it, and determines if it's antisemitic.
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Training data:
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This model was trained on 4k tweets, where ~50% were labeled as antisemitic.
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I labeled them myself based on personal experience and knowledge about common antisemitic tropes.
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Note:
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The goal for this model is not to be used as a final say on what is or is not antisemitic, but rather as a first pass on what might be antisemitic and should be reviewed by human experts.
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Please keep in mind that I'm not an expert on antisemitism or hatespeech.
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Whether something is antisemitic or not depends on the context, as for any hate speech, and everyone has a different definition for what is hate speech.
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If you would like to collaborate on antisemitism detection, please feel free to contact me at starosta@alumni.stanford.edu
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This model is not ready for production, it needs more evaluation and more training data.
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# Model Trained Using AutoNLP
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- Problem type: Binary Classification
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