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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*
  • *Corresponding author for this work
  • East China Normal University

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
JournalIEEE Transactions on Visualization and Computer Graphics
DOIs
StateAccepted/In press - 2026

Keywords

  • Authoring Tools
  • Data Videos
  • Financial Storytelling
  • Generative AI
  • Human-in-the-loop

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