Data narratives are an emerging form of communication that employs enhanced media for effective knowledge transfer of complex information. Researchers in the fields of data visualization and artificial intelligence have begun to pioneer new structures of communication to improve the efficiency of construction and the retention of information provided by the knowledge transfer experience. In this paper, we report the results of an empirical study conducted to compare the performance of various narrative communication techniques including frame based narrative visualization, documentary narrative visualization, computer generated text narratives and human generated text narratives. We assess the knowledge transfer performance for each of these data driven narrative structures. Across all conditions, an identical set of knowledge retention questions assessed participants’ recall of details from their assigned narrative communication. Statistical analysis on group performance answering the knowledge retention questions revealed that some narrative communication techniques perform better with general audiences.

数据叙述是一种新兴的交流形式，它采用增强型媒体来有效地传递复杂信息的知识。数据可视化和人工智能领域的研究人员已开始开拓新的通信结构，以提高知识转移经验提供的构建效率和保留信息的效率。在本文中，我们报告了一项实证研究的结果，以比较各种叙事传播技术的性能，包括基于框架的叙事可视化，文献叙事可视化，计算机生成的文本叙事和人工生成的文本叙事。我们评估这些数据驱动的叙述结构中每一个的知识转移性能。在所有情况下 一组相同的知识保留问题评估了参与者对他们分配的叙述性交流中细节的回忆。对小组表演的统计分析回答了知识保留问题，结果表明，某些叙事性交流技巧在普通观众中表现更好。