Qingpei Guo


2024

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HOTVCOM: Generating Buzzworthy Comments for Videos
Yuyan Chen | Songzhou Yan | Qingpei Guo | Jiyuan Jia | Zhixu Li | Yanghua Xiao
Findings of the Association for Computational Linguistics ACL 2024

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 HOTVCOM, the largest Chinese video hot-comment dataset, comprising 94k diverse videos and 137 million comments. We also present the 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.