User Generated Content
User-generated content (UGC) research focuses on understanding, analyzing, and managing the vast amount of text, images, and videos created and shared online. Current research emphasizes developing robust models for tasks such as sentiment analysis, quality assessment (including video and audio), content moderation, and summarization, often leveraging large language models (LLMs) and deep learning architectures. These advancements are crucial for improving online experiences, enhancing content recommendation systems, and addressing challenges like misinformation and harmful content, impacting both the scientific understanding of online interactions and the practical applications of AI in various industries.
Papers
AiGen-FoodReview: A Multimodal Dataset of Machine-Generated Restaurant Reviews and Images on Social Media
Alessandro Gambetti, Qiwei Han
Crowdsourced Adaptive Surveys
Yamil Velez
Spatial-Semantic Collaborative Cropping for User Generated Content
Yukun Su, Yiwen Cao, Jingliang Deng, Fengyun Rao, Qingyao Wu