| 杨雪艳,夏志杰.交互性预先干预对社交平台用户虚假信息感知和行为的影响[J].数字图书馆论坛,2024,20(11):43~51 |
| 交互性预先干预对社交平台用户虚假信息感知和行为的影响 |
| Influence of Interactive Pre-Intervention on False Information Perception and Behavior of Social Platform Users |
| 投稿时间：2024-07-05 |
| DOI：10.3772/j.issn.16732286.2024.11.005 |
| 中文关键词: 社交平台；虚假信息；预先干预；个体感知；信息行为；S-O-R框架模型 |
| 英文关键词: Social Platform; False Information; Pre-Intervention; Individual Perception; Information Behavior; S-O-R Framework Model |
| 基金项目:本研究得到国家社会科学基金一般项目“大数据支持下网络谣言智慧治理机制及运行策略研究”（编号：21BGL243）、上海市哲学社会科学规划一般项目“大数据时代伪健康信息传播特征及多主体协同干预研究”（编号：2020BGL005）资助。 |
| 作者 | 单位 | | 杨雪艳 | 上海工程技术大学管理学院 | | 夏志杰 | 上海工程技术大学管理学院 |
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| 中文摘要: |
| 通过将基于逻辑接种的预先干预措施与会话式人工智能相结合，验证智能系统驱动的交互性预先干预对社交平台用户虚假信息感知及行为（点赞和转发）的影响，为社交平台打击虚假信息提供新思路和方法。基于S-O-R理论构建研究框架模型，设计对照实验，采用问卷调查法收集数据，并通过单因素方差分析和中介效应分析探讨干预措施对用户虚假信息感知和行为的差异性影响。研究结果表明：该干预措施显著减少了虚假信息的感知可信度、感知准确性、感知真实性以及用户的点赞和转发行为；同时，感知真实性和感知准确性在干预措施与用户行为之间起到一定的中介作用。研究建议，社交平台可通过预先干预措施减少虚假信息的负面影响，并在制定干预策略时综合考虑多重因素。 |
| 英文摘要: |
| By combining logical vaccination-based pre-intervention measures with conversational artificial intelligence, the influence of intelligent systemdriven interactive pre-intervention on social platform users’ false information perception and behavior (like and forward) is verified, providing new ideas and methods for social platforms to combat false information. This study builds a framework model based on S-O-R theory, designs a control experiment, collects data by questionnaire survey, and explores the differential influence of intervention measures on users’ false information perception and behavior through oneway ANOVA and mediation effect analysis. The results show that the intervention significantly reduces the perceived credibility, accuracy, and authenticity of false information and users’ liking and forwarding behaviors. At the same time, perceived authenticity and perceived accuracy play a certain mediating role between intervention measures and user behavior. The study suggests that social platforms can reduce the negative influence of false information through preintervention measures, and take multiple factors into account when developing intervention strategies. |
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