MigrationNarrate: A Dataset for Detection of Migration Narratives in YouTube Videos

2026-08-21

AI Summary

为解决迁移叙事检测不足的问题，通过创建包含1,115个YouTube视频转录的多模态数据集MigrationNarrate，并使用预训练编码器模型和大型语言模型进行基准测试。

Abstract

Narratives are central to how social communication is framed, making their detection critical for understanding and analysing public discourse. Prior work has explored narrative detection and extraction across diverse domains; however, migration narratives remain significantly understudied, primarily due to the absence of dedicated annotated datasets. Furthermore, public communication has recently shifted towards video-centric platforms, where narratives are conveyed through multimodal signals and consumed at scale. Despite this shift, narratives in videos remain largely unexplored. To bridge these gaps, we introduce MigrationNarrate, the first multimodal dataset for detection of migration narratives in the UK, consisting of 1,115 YouTube video transcripts annotated using a two-level taxonomy of 12 migration super-narratives and 53 narrative labels. This paper details the dataset design, collection, and annotations; together with benchmark results using a combination of pre-trained encoder models and both open- and closed-source Large Language Models. Finally, a thorough error analysis offers insights for future work.

Problem

• Migration Narratives
• YouTube Videos
• Multimodal Dataset
• Public Discourse

Innovation

• multimodal dataset
• migration narratives
• YouTube videos
• two-level taxonomy
• pre-trained encoder models