增强AI生成短视频用户参与意愿：AI披露的作用

doi:10.13998/j.cnki.issn1002-1248.26-0174

Abstract

Abstract:

[Purpose/Significance] Generative AI has revitalized short video creation but blurred the line between authentic and false information. AI disclosure - informing the public of AI involvement via labels - has become a normative tool to mitigate ethical risks. However, current disclosure practices remain overly simplistic and fail to meet users' needs for transparency. How detailed disclosure labels should be designed and how they affect user cognition and behavior is still unclear. Previous studies have largely focused on the impact of whether AI is disclosed or not. Drawing on transparency design, this study further investigates the level of detail in AI disclosure. Theoretically, it confirms the importance of detailed disclosure, reveals the underlying mechanism via the heuristic-systematic model (HSM), and identifies the boundary condition of video type. Practically, it provides guidance for creators in designing disclosure labels and for platforms in effective regulation. [Method/Process] To examine the impact of AI disclosure detail on users' engagement intention, the study adopted an online experiment employing a 2×2 between-subjects experimental design to compare the effects of two types of disclosure labels across different video types. Detailed AI disclosure labels provided information regarding the type of AI technology used, its purpose, and its limitations, whereas simple AI disclosure labels merely indicated the involvement of AI technology. Additionally, the study distinguished between utilitarian and hedonic short videos for further investigation. Participants were recruited through an online experimental platform and randomly assigned to different experimental conditions. In each condition, participants were asked to view AI-generated short videos accompanied by the corresponding disclosure labels and completed a standardized questionnaire. Specifically, the questionnaire assessed participants' perceived source credibility, perceived content quality, and engagement intention, with measurement instruments adapted from validated scales. [Results/Conclusions] The study found that the level of AI disclosure detail has a significant positive effect on users' engagement intention with AI-generated short videos. Detailed AI disclosure enhances perceived content quality through the systematic route, thereby positively influencing users' engagement intention. However, the mediating role of perceived source credibility as a heuristic cue was not significant. Furthermore, this effect showed no significant difference across different types of short videos. The study provides valuable insights into the mechanisms of AI transparency. Future research can consider other dimensions of effective disclosure, explore the effects of dynamic prompts, expand sample coverage to enhance the applicability of conclusions, and conduct empirical tests incorporating actual behavioral data, thereby deepening the understanding of the mechanisms underlying AI disclosure effects.

Key words: AI-generated short videos, level of AI disclosure detail, engagement intention, perceived content quality, perceived source credibility

CLC Number:

G203

LI Jiawei, SUN Zhumo, JIANG Tingting. Enhancing User Engagement Intention in AI-Generated Short Videos: The Role of AI Disclosure[J].Journal of library and information science in agriculture, 2026, 38(7): 32-45.

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References 75

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特征	分组	数量/个	占比/%
性别	男	71	37.8
性别	女	117	62.2
年龄/岁	≤20	37	19.7
	21~30	100	53.2
	31~40	36	19.1
	41~50	10	5.3
	51~60	5	2.7
最高学历	高中生及以下	6	3.2
	大专	31	16.5
	本科	125	66.5
	研究生	26	13.8

变量	测度项	引用
兴趣	我对该视频很感兴趣	O'Brien等^[64]
实用性	我可以通过此类视频获取客观、高质量的信息	田晓旭等^[25]
	此类视频为我提供了信息和功能效能
	我可以通过此类视频实现资源获取、知识学习目标
娱乐性	我可以通过此类视频获取主观、有趣的信息
	此类视频为我提供了享乐效能
	我可以通过此类视频实现审美、愉悦及体验需求
披露透明度	我认为该标签披露了该视频使用AI技术的类型	Wang和Qiu^[14]
	我认为该标签披露了该视频使用AI技术的目的
	我认为该标签披露了该视频使用AI技术的局限性

现实情境	描述
信息获取	请想象以下场景——清晨醒来，你打开手机上的短视频应用，这时一段天气播报视频自动播放，画面中主播正用温和的声音播报今日早间天气，贴心地给出穿衣建议，你觉得这段视频信息正好能帮助你规划今天的行程，你可能会多看几秒，记住关键信息。同时请注意视频中关于使用AI技术的声明提示
娱乐放松	请想象以下场景——晚上休息时，你正在刷短视频放松，突然划到一段某地的风景视频，视频展现了该地的自然风光和人文景观，你被这些美丽的风景画面吸引，认为该视频很有趣，让你心情愉悦。同时请注意视频中关于使用AI技术的声明提示

变量	测度项	引用
感知来源可信度	我认为该视频来源是可靠的	Appelman和Sundar^[65]
	我认为该视频来源是可信的
	我认为该视频来源是权威的
感知内容质量	我认为该视频上显示的内容准确无误	Dabbous和Barakat^[58]
	我认为该视频显示的内容很有趣
	我认为该视频显示的内容很有价值
用户参与意愿	我想再次观看视频	Li和Tu^[31]
	我想“赞”视频
	我想为视频提供评论
	我会把视频分享给我的朋友

编号	假设	检验方法	结果
H1	相比于简单的AI披露，详细的AI披露会带来更高的用户参与意愿	单因素方差分析	支持
H2a	感知来源可信度在AI披露详尽程度和用户参与意愿之间起到中介作用	中介作用分析（PROCESS MODEL 4）	不支持
H2b	感知内容质量在AI披露详尽程度和用户参与意愿之间起到中介作用	中介作用分析（PROCESS MODEL 4）	支持
H3	视频类型在AI披露详尽程度和感知内容质量之间起到调节作用	调节作用分析（PROCESS MODEL 1）	不支持

Enhancing User Engagement Intention in AI-Generated Short Videos: The Role of AI Disclosure

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条件	感知来源可信度（均值±标准差）	感知内容质量（均值±标准差）	参与意愿（均值±标准差）
简单AI披露×实用型	4.86±1.35	4.70±1.23	4.21±1.62
详细AI披露×实用型	5.22±1.15	5.05±1.04	4.53±1.67
简单AI披露×享乐型	4.30±1.43	4.53±1.23	4.17±1.63
详细AI披露×享乐型	5.00±1.19	4.95±1.16	4.93±1.41

变量	均值	标准差	感知来源可信度	感知内容质量
感知来源可信度	4.85	1.32
感知内容质量	4.81	1.77	.700**
参与意愿	4.46	1.61	.564**	.728**

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