SNIL:通过大型语言模型从洞察力中生成体育新闻
IEEE transactions on visualization and computer graphics
|April 23, 2024
概括
这项研究介绍了SNIL,这是一个人工智能系统,可以从数据洞察中自动生成体育新闻. 它通过创建叙事结构和可视化,桥梁分析和沟通任务来帮助记者.
科学领域:
- 计算语言学 计算语言学
- 人与计算机的交互
- 数据新闻 数据新闻
背景情况:
- 数据新闻越来越依赖于先进的数据分析和可视化,要求更高的记者技能.
- 现有的视觉分析工具主要专注于洞察力生成,对新闻传播的支持有限.
- 弥合数据分析和沟通任务之间的差距对于有效的数据新闻创作至关重要.
研究的目的:
- 为了促进从自然语言见解中自动创建体育新闻.
- 开发一个系统,支持记者将数据洞察力转化为引人入胜的新闻内容.
- 探索一种工作流程,用于为体育新闻创建叙事结构和沟通可视化.
主要方法:
- 对已发表的体育文章进行了初步研究,以确定关键的新闻元素.
- 提出了一个四步工作流:数据空间探索,叙事结构生成,插曲创建和可视化映射.
- 实现了SNIL,一种使用大型语言模型 (LLM) 和用户输入的人类-AI交互系统.
- 启用了基于集的结构中的文本和图形内容的修改.
主要成果:
- 通过用户研究证明了SNIL系统的可用性.
- 展示了系统在弥合数据分析和沟通任务之间的差距方面的有效性.
- 收集了体育专家和球迷关于该系统的好处的积极反.
结论:
- 斯尼尔有效地支持从数据洞察力中自动生成体育新闻.
- 人与人工智能交互的方法增强了创建有信息和有吸引力的数据新闻的方法.
- 该系统为记者提供了宝贵的工具,简化了从数据分析到新闻传播的过程.
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