基于多模态特征构建预测短视频感官与行为参与的计算模型
A Computational Model of Message Sensation Value in Short Video Multimodal Features that Predicts Sensory and Behavioral Engagement
- 融合多模态特征与人类评估，建立消息感官价值计算模型
- 高感官价值提升感官参与，中等感官价值最优化行为参与
- 适用于短视频平台内容推荐与创作优化研究
当前媒体环境以煽动性短视频为主。尽管先前研究探讨了单一多模态特征的影响，但多模态特征对观众参与度的综合效应仍不明确。基于消息感官价值（MSV）理论框架，本研究通过分析1,200条短视频的多模态特征并结合人工评估，构建并验证了一个预测感官与行为参与的计算模型。该模型在来自三个短视频平台的两个未见数据集（总计N=14,492）上得到进一步验证。结果表明，MSV与感官参与呈正相关，但与行为参与呈现倒U型关系：更高的MSV带来更强感官刺激，而中等水平的MSV最能优化行为参与。该研究深化了对短视频参与机制的理论理解，并提供了一个稳健的计算工具用于短视频研究。
原文摘要 · Abstract (English)
The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal features, the collective impact of multimodal features on viewer engagement with short videos remains unknown. Grounded in the theoretical framework of Message Sensation Value (MSV), this study develops and tests a computational model of MSV with multimodal feature analysis and human evaluation of 1,200 short videos. This model that predicts sensory and behavioral engagement was further validated across two unseen datasets from three short video platforms (combined N = 14,492). While MSV is positively associated with sensory engagement, it shows an inverted U-shaped relationship with behavioral engagement: Higher MSV elicits stronger sensory stimulation, but moderate MSV optimizes behavioral engagement. This research advances the theoretical understanding of short video engagement and introduces a robust computational tool for short video research.
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