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Persuasion techniques detection in news in a multi-lingual setup isnon-trivial and comes with challenges, including little training data. Oursystem successfully leverages (back-)translation as data augmentationstrategies with multi-lingual transformer models for the task of detectingpersuasion techniques. The automatic and human evaluation of our augmented dataallows us to explore whether (back-)translation aid or hinder performance. Ourin-depth analyses indicate that both data augmentation strategies boostperformance; however, balancing human-produced and machine-generated data seemsto be crucial.

NAP at SemEval-2023 Task 3: Is Less Really More? (Back-)Translation as Data Augmentation Strategies for Detecting Persuasion Techniques