“解读”抑或“留白”:数据新闻语图结构的认知效果研究

"Explaining"or"Leaving Blank":A Study on the Cognitive Effects of Different Syntactic-Graphical Content Structures in Data Journalism

随着数据与可视化技术不断发展,数据图表常现于新闻报道,与文字共同传达信息。在种种新闻体裁中,数据新闻最能直接体现语图内容结构之间的配合。本研究以LC4MP为理论框架,基于对76名被试的实验研究,测量数据新闻中五种语图内容结构(图表统摄、文字统摄、语图重合、语图对话、语图协商)在三个认知阶段(编码、存储、回想)的认知效果差异。研究结果显示,不同语图结构在不同认知阶段效果差异明显,文字统摄的短期认知最佳,最有助于长期记忆的内容结构是语图重合和文字统摄。研究进一步评估了读者长期记忆中的信息质量,发现语图重合与文字统摄结构使读者认知的信息质量整体上更高。值得一提的是,图表统摄会让读者记住更多中心信息,也有利于读者对信息的再应用,促进新闻报道内容的知识化。文字在受到新技术冲击的情况下仍处于数据新闻的“招牌”地位。根据对不同类别信息的传播效果期望,新闻制作者可选择合适的内容结构进行灵活组合。

This research evaluates the cognitive impacts of five text-graphic structures within data journalism—graph-dominated,text-dominated,overlapping,dialogue,and negotiation—on encoding,storage,and retrieval processes,through an experiment with 76 participants.Anchored in the LC4MP theoretical framework,the study uncovers significant variance in cognitive processing based on the content structure.Specifically,text-dominated structures excel in fostering short-term cognitive performance,whereas overlapping and text-dominated arrangements are more effective for enhancing long-term memory and improving overall information quality.Notably,graph-dominated structures are particularly efficient at aiding the recall of central information,thus facilitating the deeper assimilation of news content into knowledge.Despite technological advancements,this study reaffirms the critical role of text in data journalism and suggests that news producers can optimize information dissemination by strategically selecting and combining content structures to match intended cognitive outcomes.