ShortCheck: Checkworthiness Detection of Multilingual Short-Form Videos

Henrik Vatndal, Vinay Setty
9/24/2025
cs.CLcs.CV

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Abstract

Short-form video platforms like TikTok present unique challenges for misinformation detection due to their multimodal, dynamic, and noisy content. We present ShortCheck, a modular, inference-only pipeline with a user-friendly interface that automatically identifies checkworthy short-form videos to help human fact-checkers. The system integrates speech transcription, OCR, object and deepfake detection, video-to-text summarization, and claim verification. ShortCheck is validated by evaluating it on two manually annotated datasets with TikTok videos in a multilingual setting. The pipeline achieves promising results with F1-weighted score over 70\%.

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Cite this paper

@article{vatndal2025shortcheck,
  title  = {ShortCheck: Checkworthiness Detection of Multilingual Short-Form Videos},
  author = {Henrik Vatndal and Vinay Setty},
  year   = {2025},
  eprint = {2509.20467},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2509.20467v1}
}

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