@inproceedings{sung-etal-2023-fake,
    title = "Not all Fake News is Written: A Dataset and Analysis of Misleading Video Headlines",
    author = "Sung, Yoo Yeon  and
      Boyd-Graber, Jordan  and
      Hassan, Naeemul",
    editor = "Bouamor, Houda  and
      Pino, Juan  and
      Bali, Kalika",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2023.emnlp-main.1010/",
    doi = "10.18653/v1/2023.emnlp-main.1010",
    pages = "16241--16258",
    abstract = "Polarization and the marketplace for impressions have conspired to make navigating information online difficult for users, and while there has been a significant effort to detect false or misleading text, multimodal datasets have received considerably less attention. To complement existing resources, we present multimodal Video Misleading Headline (VMH), a dataset that consists of videos and whether annotators believe the headline is representative of the video{'}s contents. After collecting and annotating this dataset, we analyze multimodal baselines for detecting misleading headlines. Our annotation process also focuses on why annotators view a video as misleading, allowing us to better understand the interplay of annotators' background and the content of the videos."
}