摘要
[目的/意义]探究平台特征对跨社交媒体UGC信息分享行为的影响,揭示用户跨社交媒体场景的新特征。[方法/过程]通过刺激—机体—反应(SOR)理论框架构建平台特征对跨社交媒体UGC信息分享行为的中介调节模型,以时间维度和平台维度拼接应用商城数据、百度指数数据、社交媒体数据等,构建多源异构面板数据集作为样本,使用固定效应模型验证相关假设。[结果/结论]平台的声誉和用户服务技术迭代通过感知有用性正向影响跨社交媒体UGC信息分享,而平台的关注度通过感知有用性显著负向影响信息分享行为;平台声誉和用户服务技术迭代对感知有用性和跨社交媒体UGC信息分享之间的关系具有负向调节作用。本文关注跨社交媒体UGC的信息分享行为,为UGC创作者采用跨社交媒体信息投放策略提供参照,为社交媒体维护平台生态提供启示。
[Purpose/Significance]This research aims to explore the impact of platform characteristics on User-Generated Content(UGC)sharing behavior across social media platforms,revealing new features of user behavior in cross-social media scenarios.[Method/Process]Drawing from the Stimulus-Organism-Response(SOR)theoretical framework,the study constructed a mediating model to understand the influence of platform characteristics on cross-social media UGC sharing behavior.The paper integrated data from application stores,Baidu Index,and social media across time and platform dimensions,created a multi-source heterogeneous panel dataset as our sample.The hypotheses were tested to use a fixed-effects model.[Results/Conclusion]The platform's reputation and the iterative advancements in user service technology positively influence cross-social media UGC sharing through perceived usefulness.Conversely,the platform's attention level negatively affects sharing behavior via perceived usefulness.Moreover,the platform's reputation and iterative advancements in user service technology have a negative moderating effect on the relationship between perceived usefulness and cross-social media UGC sharing.This study focuses on the sharing behavior of UGC across social media platforms,offering insights for UGC creators to adopt cross-platform content dissemination strategies and providing guidance for social media platforms to maintain a balanced ecosystem.
作者
黄伟鑫
毕达天
杨阳
孔婧媛
Huang Weixin;Bi Datian;Yang Yang;Kong Jingyuan;无(School of Business and Management,Jilin University,Changchun 130012,China;School of Marxism,Jilin University of Arts,Changchun 130012,China)
出处
《现代情报》
CSSCI
北大核心
2024年第2期115-129,共15页
Journal of Modern Information
基金
国家社会科学基金一般项目“基于用户跨社交媒体的信息行为偏好特征挖掘与推荐研究”(项目编号:21BTQ059)。
