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NewsVis: GenAI-based Visual Storytelling for Corporate Financial News

  • Jia Bu
  • , Mingwei Jiang
  • , Shuqi Liu
  • , Tong Lyu
  • , Lumeng Wu
  • , Shiqi Jiang
  • , Boyuan Huangfu
  • , Changbo Wang
  • , Chenhui Li*
  • *此作品的通讯作者
  • East China Normal University

科研成果: 期刊稿件文章同行评审

摘要

Corporate financial news is pivotal for market decisions, but often overwhelms general audiences. While data videos effectively bridge this comprehension gap, their production remains a bottleneck for journalists. We present NewsVis, an authoring tool powered by Generative Artificial Intelligence (GenAI) that automates the transformation of unstructured narratives and raw financial datasets into professional data videos. Unlike generic models, our pipeline ensures factual accuracy through a domain-specific taxonomy of financial attributes and optimizes visual information presentation via a multimodal layout algorithm. Additionally, a human-in-the-loop interface empowers journalists to audit and calibrate generative outputs. Comprehensive quantitative and qualitative evaluations demonstrate that NewsVis significantly reduces production barriers while enhancing information accessibility for viewers.

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