HOTVCOM: Generating Buzzworthy Comments for Videos

• URL: http://arxiv.org/abs/2409.15196v1
• Date: Mon, 23 Sep 2024 16:45:13 GMT
• Title: HOTVCOM: Generating Buzzworthy Comments for Videos
• Authors: Yuyan Chen, Yiwen Qian, Songzhou Yan, Jiyuan Jia, Zhixu Li, Yanghua Xiao, Xiaobo Li, Ming Yang, Qingpei Guo,
• Abstract summary: This study introduces textscHotVCom, the largest Chinese video hot-comment dataset, comprising 94k diverse videos and 137 million comments. We also present the textttComHeat framework, which synergistically integrates visual, auditory, and textual data to generate influential hot-comments on the Chinese video dataset.
• Score: 49.39846630199698
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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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