Abstract

This article aims to explain learning outcomes of incidental exposure (IE) to political information in online environments. Drawing on the Political Incidental News Exposure Model, we predict learning outcomes by distinguishing between first-level (i.e., scanning of incidentally encountered information) and second-level IE (i.e., effortful processing of incidentally encountered information appraised as relevant). Furthermore, we conceptualize intention-based IE (i.e., while looking for non-political content) and topic-based IE (i.e., while looking for different political content). In a 2x2 experiment (N = 290), we manipulated respondents’ initial processing goal (i.e., political or non-political information) and low (i.e., first-level IE) versus high (i.e., second-level IE) relevance of the incidentally encountered information. Results show stronger learning effects for second level than for first-level IE. Learning effects do not differ between topic-based and intention-based IE, but second-level IE decreases learning related to the initial processing goal. Theoretical implications are discussed.

中文翻译：

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在线环境中从偶然接触政治信息中学习

摘要

本文旨在解释在线环境中政治信息的偶然暴露（IE）的学习成果。利用“政治偶然新闻暴露模型”，我们通过区分第一级（即，扫描偶然遇到的信息）和第二级IE（即，对相关评估认为是偶然处理的偶然信息进行处理）来预测学习结果。此外，我们将基于意图的IE（即，寻找非政治内容）和基于主题的IE（即，寻找不同的政治内容）概念化。在2x2实验中（N  = 290），我们操纵了受访者的初始处理目标（即政治或非政治信息）和偶然遇到的信息的低（即第一级IE）与高（即第二级IE）的相关性。结果显示，与第一级IE相比，第二级的学习效果更强。基于主题的IE和基于意图的IE的学习效果没有区别，但是第二级IE会减少与初始处理目标相关的学习。理论意义进行了讨论。