HOTVCOM: Generating Buzzworthy Comments for Videos

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 $\text{textsc}HotVCom$, the largest Chinese video hot-comment dataset, comprising 94k diverse videos and 137 million comments. We also present the $\mathtt{\text{ComHeat}}$ 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.