推算法的信息流对目标广告受众应对行为的影响
Lijun Chen1, Rui Sun2, Yuan Yuan2
1School of Business Administration, Huaqiao University, Quanzhou 362021, China; School of Business Administration, Jimei University, Xiamen 361021, China.
Acta psychologica
|February 3, 2024
概括
针对性广告中的算法透明度会影响用户应对行为. 从信息流特征感知到的信任和威胁,以自我效能为调节,决定了这些行为,为个性化建议提供了洞察力.
科学领域:
- 消费者行为 消费者行为
- 算法说服力是一种说服力.
- 信息流动动态 信息流动动态
背景情况:
- 定向广告使用推算法来匹配用户内容.
- 过于精确的建议可能会引发观众的负面反应.
- 建议对算法进行透明化,以缓解担忧并建立信任.
研究的目的:
- 调查算法推透明度和受众应对行为之间的关系.
- 探索信息流特征对有针对性的广告应对行为的影响.
- 应用说服理论来理解算法推效应.
主要方法:
- 利用说服理论来分析信息流动模式和传输原则.
- 进行了120次在线预测和297次正式测试.
- 检查了感知到的信任和威胁的调解作用,以及自我效能的调节作用.
主要成果:
- 算法推的信息流特征影响观众应对行为.
- 感知到的信任和感知到的威胁共同决定了应对行为.
- 用户的自我效能调节了心理过程和应对行为之间的联系.
结论:
- 这项研究阐明了推算法信息流和受众应对行为之间的联系.
- 这些发现丰富了算法说服框架,并为个性化推的有效性提供了价值.
- 为平台和广告商提供有关透明度和消费者行为的实用建议.
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