构建中文视频热评数据集并生成有影响力的评论。
HOTVCOM: Generating Buzzworthy Comments for Videos
- 融合视觉、音频和文本信息生成热评
- 涵盖94万视频与1.37亿条评论
- 适合短视频营销与内容推荐场景
在社交媒体视频平台时代，热门评论对吸引用户关注短视频至关重要，具有重要的营销与品牌价值。然而，现有研究多聚焦于生成英文描述性评论或弹幕，仅对视频特定时刻做出即时反应。针对这一空白，本研究提出 extsc{HotVCom}，目前最大的中文视频热评数据集，包含94万部多样化视频与1.37亿条评论。我们还提出了 exttt{ComHeat} 框架，通过协同整合视觉、听觉和文本数据，在该中文数据集上生成具有影响力的热评。实证评估表明，该框架在新构建及现有数据集上均表现出色。
原文摘要 · Abstract (English)
In the era of social media video platforms, popular ``hot-comments'' play a crucial role in attracting user impressions of short-form videos, making them vital for marketing and branding purpose. However, existing research predominantly focuses on generating descriptive comments or ``danmaku'' in English, offering immediate reactions to specific video moments. Addressing this gap, our study introduces \textsc{HotVCom}, the largest Chinese video hot-comment dataset, comprising 94k diverse videos and 137 million comments. We also present the \texttt{ComHeat} framework, which synergistically integrates visual, auditory, and textual data to generate influential hot-comments on the Chinese video dataset. Empirical evaluations highlight the effectiveness of our framework, demonstrating its excellence on both the newly constructed and existing datasets.
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