Datasets:
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README.md
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dtype: int64
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- name: sa
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dtype: int64
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- name: __index_level_0__
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dtype: int64
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splits:
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- name: train
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num_bytes:
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num_examples: 1613790
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- name: test
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num_bytes:
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num_examples: 448276
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- name: dev
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num_bytes:
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num_examples: 179310
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download_size:
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dataset_size:
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---
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The Moji dataset (Blodgett et al., 2016) (http://slanglab.cs.umass.edu/TwitterAAE/) contains tweets used for sentiment analysis (either positive or negative sentiment), with additional information on the type of English used in the tweets which is a sensitive attribute considered in fairness-aware approaches (African-American English (AAE) or Standard-American English (SAE)).
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dtype: int64
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- name: sa
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dtype: int64
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splits:
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- name: train
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num_bytes: 128596235
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num_examples: 1613790
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- name: test
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num_bytes: 35731728
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num_examples: 448276
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- name: dev
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num_bytes: 14325121
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num_examples: 179310
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download_size: 93470968
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dataset_size: 178653084
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---
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The Moji dataset (Blodgett et al., 2016) (http://slanglab.cs.umass.edu/TwitterAAE/) contains tweets used for sentiment analysis (either positive or negative sentiment), with additional information on the type of English used in the tweets which is a sensitive attribute considered in fairness-aware approaches (African-American English (AAE) or Standard-American English (SAE)).
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