ComVi: Context-Aware Optimized Comment Display in Video Playback
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866910077943808000 |
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| author | Kim, Minsun Lee, Dawon Noh, Junyong |
| author_facet | Kim, Minsun Lee, Dawon Noh, Junyong |
| contents | On general video-sharing platforms like YouTube, comments are displayed independently of video playback. As viewers often read comments while watching a video, they may encounter ones referring to moments unrelated to the current scene, which can reveal spoilers and disrupt immersion. To address this problem, we present ComVi, a novel system that displays comments at contextually relevant moments, enabling viewers to see time-synchronized comments and video content together. We first map all comments to relevant video timestamps by computing audio-visual correlation, then construct the comment sequence through an optimization that considers temporal relevance, popularity (number of likes), and display duration for comfortable reading. In a user study, ComVi provided a significantly more engaging experience than conventional video interfaces (i.e., YouTube and Danmaku), with 71.9% of participants selecting ComVi as their most preferred interface. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_26173 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ComVi: Context-Aware Optimized Comment Display in Video Playback Kim, Minsun Lee, Dawon Noh, Junyong Multimedia Computer Vision and Pattern Recognition Graphics Human-Computer Interaction H.5.2 On general video-sharing platforms like YouTube, comments are displayed independently of video playback. As viewers often read comments while watching a video, they may encounter ones referring to moments unrelated to the current scene, which can reveal spoilers and disrupt immersion. To address this problem, we present ComVi, a novel system that displays comments at contextually relevant moments, enabling viewers to see time-synchronized comments and video content together. We first map all comments to relevant video timestamps by computing audio-visual correlation, then construct the comment sequence through an optimization that considers temporal relevance, popularity (number of likes), and display duration for comfortable reading. In a user study, ComVi provided a significantly more engaging experience than conventional video interfaces (i.e., YouTube and Danmaku), with 71.9% of participants selecting ComVi as their most preferred interface. |
| title | ComVi: Context-Aware Optimized Comment Display in Video Playback |
| topic | Multimedia Computer Vision and Pattern Recognition Graphics Human-Computer Interaction H.5.2 |
| url | https://arxiv.org/abs/2603.26173 |