HOTVCOM: Generating Buzzworthy Comments for Videos

TL;DR

This paper introduces HotVCom, a large Chinese video hot-comment dataset, and ComHeat, a multimodal framework that generates influential comments to enhance user engagement on social media videos.

Contribution

It presents the largest Chinese hot-comment dataset and a novel multimodal framework for generating impactful comments, addressing a gap in existing research.

Findings

ComHeat outperforms baseline models in generating hot-comments.

The dataset enables better understanding of Chinese social media comments.

Empirical results validate the effectiveness of the multimodal approach.

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.