twitter_hate_speech_detection

ds = tfds.load('huggingface:tweets_hate_speech_detection')

The objective of this task is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets.

Formally, given a training sample of tweets and labels, where label ‘1’ denotes the tweet is racist/sexist and label ‘0’ denotes the tweet is not racist/sexist, your objective is to predict the labels on the given test dataset.

{
    "label": {
        "num_classes": 2,
        "names": [
            "no-hate-speech",
            "hate-speech"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "tweet": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}