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ChatGPT outperforms crowd workers for text-annotation tasks

ChatGPT outperforms crowd workers for text-annotation tasks Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd workers on platforms such as MTurk as well as trained annotators, such as research assistants. Using four samples of tweets and news articles ( n = 6,183), we show that ChatGPT outperforms crowd w...

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ChatGPT outperforms crowd workers for text-annotation tasks | Awareness Public Knowledge