Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories
English summary
The paper proposes Data2Story, a multi-agent framework that automates data journalism by mimicking a virtual newsroom with distinct roles. It generates evidence-based news stories in multiple formats, such as text articles, interactive maps, and audio, each linked to data sources for verifiability. In evaluations against expert human journalists, Data2Story showed competitive performance, particularly excelling in transparency and auditability. Human journalists still outperform in editorial angle and creative design. The system is designed as a collaborative tool for journalists, not a replacement.
Chinese summary
该论文提出了Data2Story，一个通过模拟虚拟新闻编辑室中不同角色的多智能体框架，来自动化数据新闻生产。它能够生成基于证据的多格式新闻故事，包括文字报道、交互地图和音频，并链接数据源以确保可验证性。在与人类专家记者的对比评估中，Data2Story展现出有竞争力的表现，尤其在透明度和可审计性方面突出，但人类记者在编辑角度和创意设计方面仍占优势。该系统被定位为记者的协作工具。
Key points
Data2Story is a multi-agent framework that automates data journalism by assigning different roles in a virtual newsroom.
Data2Story是一个多智能体框架，通过在虚拟新闻编辑室中分配不同角色自动化数据新闻生产。
It generates multimodal stories (text, interactive maps, audio) linked to external data sources for verifiability.
它生成多模态故事（文字、交互地图、音频），并链接外部数据源，确保可验证性。
Evaluated against human experts, the system was competitive and especially strong in transparency and auditability.
在与人类专家的对比评估中，该系统具有竞争力，尤其在透明度和可审计性方面表现突出。
Human journalists still lead in editorial angle and creative design, but the tool is intended for collaboration.
人类记者在编辑角度和创意设计上仍领先，但该工具旨在用于协作，而非替代。