Summary of Infer Induced Sentiment Of Comment Response to Video: a New Task, Dataset and Baseline, by Qi Jia et al.
Infer Induced Sentiment of Comment Response to Video: A New Task, Dataset and Baseline
by Qi Jia, Baoyu Fan, Cong Xu, Lu Liu, Liang Jin, Guoguang Du, Zhenhua Guo, Yaqian Zhao, Xuanjing Huang, Rengang Li
First submitted to arxiv on: 15 May 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In a novel approach to multi-modal sentiment analysis, researchers introduce MSA-CRVI, a task that aims to infer opinions and emotions based on comments responding to micro videos. This study focuses on the induced sentiment of viewers while watching videos, which is crucial for understanding public response to content, advertising effectiveness, and societal sentiment analysis. A large-scale dataset, CSMV, is manually annotated with 107,267 comments and 8,210 micro videos totaling 68.83 hours, supporting this research. The proposed Video Content-aware Comment Sentiment Analysis (VC-CSA) method serves as a baseline to address the challenges in this new task, demonstrating significant improvements over established baselines. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study explores how people respond to short videos and what emotions those responses evoke. It’s like trying to understand how people react to funny memes or viral videos on social media! The researchers created a massive dataset of comments and videos to help them figure out how to do this better. They came up with a new way to analyze these comments, called VC-CSA, which is more accurate than other methods. This research has big implications for understanding how people respond to different types of content and even how effective advertisements are. |
Keywords
» Artificial intelligence » Multi modal
