复旦大学国家智能评价与治理实验基地赵星教授团队硕士研究生钱鹏博，以第一作者身份在SSCI & SCI Q1期刊《人机交互国际期刊》（International Journal of Human–Computer Interaction）上发表了题为《探究AI主播形象与新闻内容一致性在Z世代新闻观看体验中的作用：一项基于中国情境的混合方法研究》（Exploring the Role of AI Anchor Image-News Content Congruency in News-Viewing Experience Among Gen Zers: A Mixed-Method Study in the Chinese Context）的研究论文。该研究不仅拓展了媒体一致性理论在AI传播语境下的内涵，而且为针对Z世代的AI主播形象设计与新闻内容匹配策略提供了实证依据与优化思路，对提升智能媒体的传播效能具有重要的理论与实践意义。

摘要：The rise of AI technology in news broadcasting marks a significant change in information delivery, particularly for Gen Zers with unique media format preferences. While AI anchors aim to boost engagement, their effectiveness is often questioned due to inadequate implementations. This study posits that the success of AI anchors depends on the congruency between AI images and news content. Through a mixed-method investigation, we examine how different combinations of AI anchor images and news contents influence Gen Zers’ news-viewing experiences. The findings reveal that hyper-simulation anchors facilitate experiential engagement with soft news while hyper-realization anchors enable more comprehensive cognitive processing of hard news through perceived credibility. These effects are mediated by three fundamental mechanisms – processing alignment, emotional resonance, and perceived credibility. This research expands media congruency theory, offering strategic insights for optimizing AI anchor designs to better engage Gen Zers.

关键词：AI anchor; congruency effect; news-viewing experience; mixed-method

DOI：https://doi.org/10.1080/10447318.2025.2542902

收录数据库：Web of Science