Distorted science communication harms individuals and society as it can lead to unhealthy behavior change and decrease trust in scientific institutions. Given the rapidly increasing volume of science communication in recent years, a fine-grained understanding of how findings from scientific publications are reported to the general public, and methods to detect distortions from the original work automatically, are crucial. This dataset contains  1,600 instances of scientific findings from academic papers paired with corresponding findings as reported in news articles and tweets annotated wrt. four characteristics: causality, certainty, generality and sensationalism.

Amelie Wuehrl, Dustin Wright, Roman Klinger, Isabelle Augenstein: Understanding Fine-grained Distortions in Reports of Scientific Findings. ACL Findings 2024.
A preprint of the paper is available at https://arxiv.org/abs/2402.12431.

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