FakingRecipe：从创作过程视角检测短视频平台上的假新闻
FakingRecipe: Detecting Fake News on Short Video Platforms from the Perspective of Creative Process
AI总结：
针对短视频假新闻多模态异构信息检测难题，提出从创作过程视角分析素材选择与编辑特征的FakingRecipe模型，并构建英文数据集FakeTT，在多数据集实验中验证了其优越性。
摘要：
随着短视频分享平台成为新闻消费的重要渠道，短视频中的假新闻已成为在线信息生态系统的严重威胁，这使得开发针对这一新场景的检测方法成为迫切需求。与文本和图像格式相比，短视频平台上的假新闻在多种模态中包含丰富但异构的信息，对有效特征利用构成了挑战。现有工作大多集中于分析“呈现了什么”，与此不同，我们引入了一个考虑“可能是如何创作的”新视角。通过新闻视频制作背后创作过程的视角，我们的实证分析揭示了假新闻视频在素材选择和编辑方面的独特特征。基于所获得的见解，我们设计了FakingRecipe，一个感知创作过程的假新闻短视频检测模型。它从情感和语义方面捕捉素材选择中的假新闻偏好，并从空间和时间方面考虑素材编辑的特征。为了提高评估的全面性，我们首先构建了用于该任务的英文数据集FakeTT，并在FakeTT和现有的中文数据集FakeSV上进行了实验。结果表明，FakingRecipe在检测短视频平台上的假新闻方面具有优越性。
英文摘要：
As short-form video-sharing platforms become a significant channel for news consumption, fake news in short videos has emerged as a serious threat in the online information ecosystem, making developing detection methods for this new scenario an urgent need. Compared with that in text and image formats, fake news on short video platforms contains rich but heterogeneous information in various modalities, posing a challenge to effective feature utilization. Unlike existing works mostly focusing on analyzing what is presented, we introduce a novel perspective that considers how it might be created. Through the lens of the creative process behind news video production, our empirical analysis uncovers the unique characteristics of fake news videos in material selection and editing. Based on the obtained insights, we design FakingRecipe, a creative process-aware model for detecting fake news short videos. It captures the fake news preferences in material selection from sentimental and semantic aspects and considers the traits of material editing from spatial and temporal aspects. To improve evaluation comprehensiveness, we first construct FakeTT, an English dataset for this task, and conduct experiments on both FakeTT and the existing Chinese FakeSV dataset. The results show FakingRecipe's superiority in detecting fake news on short video platforms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
