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言辞之道:措辞选择对信息参与度与决策的影响

The Ways of Words: The Impact of Word Choice on Information Engagement and Decision Making

State University of New York at Albany(纽约州立大学奥尔巴尼分校);Google(谷歌公司)

Nimrod Dvir, Elaine Friedman, Suraj Commuri, Fan Yang, Jennifer Romano

AI总结:

本研究综合UET和IBT理论构建框架,通过大规模用户实验验证措辞选择对信息参与度(IE)感知、参与和坚持三维度及决策的显著影响,提出了评估与改进数字文本IE和决策的方法。

摘要:

鲜有研究探讨信息参与度(IE),即个体以认知、行为和情感方式互动并使用信息的程度。本研究探讨了措辞,特别是措辞选择,对IE和决策的影响。综合用户参与理论(UET)和信息行为理论(IBT)两个理论模型,开发了一个理论框架,阐明了感知、参与和坚持这三个IE维度的影响及其相互关系,并提出了假设。该框架在一项大规模用户研究中得到了实证验证,测量了措辞选择如何影响IE的各个维度。研究结果表明,IE不同于其他形式的参与,它是由信息本身的表达所驱动和促进的,无论使用何种信息系统来查看、互动和使用信息。研究结果表明,措辞会对数字信息的解释和互动产生重大影响,表明信息表达,特别是措辞选择,对决策和IE具有重要性。本研究通过识别评估和改进IE及数字文本决策的方法,为文献做出了贡献。

英文摘要:

Little research has explored how information engagement (IE), the degree to which individuals interact with and use information in a manner that manifests cognitively, behaviorally, and affectively. This study explored the impact of phrasing, specifically word choice, on IE and decision making. Synthesizing two theoretical models, User Engagement Theory UET and Information Behavior Theory IBT, a theoretical framework illustrating the impact of and relationships among the three IE dimensions of perception, participation, and perseverance was developed and hypotheses generated. The framework was empirically validated in a large-scale user study measuring how word choice impacts the dimensions of IE. The findings provide evidence that IE differs from other forms of engagement in that it is driven and fostered by the expression of the information itself, regardless of the information system used to view, interact with, and use the information. The findings suggest that phrasing can have a significant effect on the interpretation of and interaction with digital information, indicating the importance of expression of information, in particular word choice, on decision making and IE. The research contributes to the literature by identifying methods for assessment and improvement of IE and decision making with digital text.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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