We contribute the first publicly available dataset of factual claims from different platforms and fake YouTube videos on the 2023 Israel-Hamas war for automatic fake YouTube video classification. The FakeClaim data is collected from 60 fact-checking organizations in 30 languages and enriched with metadata from the fact-checking organizations curated by trained journalists specialized in fact-checking. Further, we classify fake videos within the subset of YouTube videos using textual information and user comments. We used a pre-trained model to classify each video with different feature combinations. Our best-performing fine-tuned language model, Universal Sentence Encoder (USE), achieves a Macro F1 of 87\%, which shows that the trained model can be helpful for debunking fake videos using the comments from the user discussion. The dataset is available on Github\footnote{https://github.com/Gautamshahi/FakeClaim}

翻译：我们贡献了首个公开可用的数据集，包含来自不同平台的事实声明与2023年以色列-哈马斯战争中虚假YouTube视频，用于自动分类虚假YouTube视频。FakeClaim数据采集自30种语言的60个事实核查机构，并由经过培训、专攻事实核查的记者策划，补充了这些机构提供的元数据。进一步地，我们利用文本信息和用户评论对YouTube视频子集中的虚假视频进行分类。我们使用预训练模型，结合不同特征组合对每个视频进行分类。性能最佳的微调语言模型——通用句子编码器（USE），在宏F1分数上达到87%，表明该训练模型可借助用户讨论中的评论有效帮助识别虚假视频。该数据集可在GitHub上获取\footnote{https://github.com/Gautamshahi/FakeClaim}。