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.
Cite
@article{arxiv.2409.15196,
title = {HOTVCOM: Generating Buzzworthy Comments for Videos},
author = {Yuyan Chen and Yiwen Qian and Songzhou Yan and Jiyuan Jia and Zhixu Li and Yanghua Xiao and Xiaobo Li and Ming Yang and Qingpei Guo},
journal= {arXiv preprint arXiv:2409.15196},
year = {2024}
}