<ul><li>Dark patterns are user interface designs in online services that induce users to take unintended actions.</li><li>A dataset for dark pattern detection has been constructed, consisting of 1,818 dark pattern texts from shopping sites.</li><li>State-of-the-art machine learning methods like BERT, RoBERTa, ALBERT, and XLNet have been applied to demonstrate automatic detection accuracy as baselines.</li><li>RoBERTa achieved the highest accuracy of 0.975 in the 5-fold cross-validation.</li></ul>

Dark patterns in e-commerce: a dataset and its baseline evaluations

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