- Author
- Quanqi Du (UGent) , Sofie Labat (UGent) , Thomas Demeester (UGent) and Veronique Hoste (UGent)
- Organization
- Project
- Abstract
- UniC: a Dataset for Emotion Analysis of Videos with Multimodal and Unimodal Labels UniC is comprised of 965 emotion-rich video clips selected from YouTube, annotated in text, audio, (silent) video and multimodal setups with both categorical and dimensional labels. Categorical label: disgust, disappointment, neutral, confusion, surprise, contentment, and joy. Dimensional label: Valence and arousal.
- Keywords
- text, audio, video, sentiment and emotion modeling, unimodal and multimodal labels, youtube, review, sentiment analysis
- License
- CC-BY-NC-SA-4.0
- Access
- closed access
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01KCBDT69W2QKPSPTFFX749DV7
@misc{01KCBDT69W2QKPSPTFFX749DV7,
abstract = {{UniC: a Dataset for Emotion Analysis of Videos with Multimodal and Unimodal Labels
UniC is comprised of 965 emotion-rich video clips selected from YouTube, annotated in text, audio, (silent) video and multimodal setups with both categorical and dimensional labels.
Categorical label: disgust, disappointment, neutral, confusion, surprise, contentment, and joy.
Dimensional label: Valence and arousal.}},
author = {{Du, Quanqi and Labat, Sofie and Demeester, Thomas and Hoste, Veronique}},
keywords = {{text,audio,video,sentiment and emotion modeling,unimodal and multimodal labels,youtube,review,sentiment analysis}},
language = {{eng}},
publisher = {{LT3, Ghent University}},
title = {{UniC: A Dataset for Emotion Analysis of Videos With Multimodal and Unimodal Labels}},
year = {{2025}},
}