构建韩语现代诗情感数据集，支持情感分析与生成。
KPoEM: A Human-Annotated Dataset for Emotion Classification and RAG-Based Poetry Generation in Korean Modern Poetry
- 人工标注7662条诗句/作品，涵盖44类情绪标签。
- 情感分类模型F1-micro达0.60，显著优于之前的0.43。
- 结合RAG实现有文化情感的诗歌生成，适合文学计算研究者。
本研究提出KPoEM（韩语诗歌情感映射）数据集，为现代韩语诗歌的情感分析与生成应用提供基础。尽管自然语言处理取得进展，诗歌因复杂的修辞和文化特异性仍被低估。我们构建了包含7,662条记录（7,007行级、615作品级）的多标签数据集，由五位重要韩语诗人作品构成，标注44种细粒度情绪类别。基于顺序微调策略（从通用语料到KPoEM），KPoEM情感分类模型在测试中获得0.60的F1-micro得分，显著优于此前模型的0.43。该模型更擅长识别时间与文化特定的情绪表达，同时保留核心诗意情感。进一步将结构化情绪数据应用于基于RAG的诗歌生成模型，验证了生成具有韩语文学情感与文化敏感性的文本的可行性。此整合方法强化了计算技术与文学分析的联系，为定量情感研究与生成诗学开辟新路径。整体而言，本研究为推进现代韩语诗歌的情感中心分析与创作奠定了基础。
原文摘要 · Abstract (English)
This study introduces KPoEM (Korean Poetry Emotion Mapping), a novel dataset that serves as a foundation for both emotion-centered analysis and generative applications in modern Korean poetry. Despite advancements in NLP, poetry remains underexplored due to its complex figurative language and cultural specificity. We constructed a multi-label dataset of 7,662 entries (7,007 line-level and 615 work-level), annotated with 44 fine-grained emotion categories from five influential Korean poets. The KPoEM emotion classification model, fine-tuned through a sequential strategy -- moving from general-purpose corpora to the specialized KPoEM dataset -- achieved an F1-micro score of 0.60, significantly outperforming previous models (0.43). The model demonstrates an enhanced ability to identify temporally and culturally specific emotional expressions while preserving core poetic sentiments. Furthermore, applying the structured emotion dataset to a RAG-based poetry generation model demonstrates the empirical feasibility of generating texts that reflect the emotional and cultural sensibilities of Korean literature. This integrated approach strengthens the connection between computational techniques and literary analysis, opening new pathways for quantitative emotion research and generative poetics. Overall, this study provides a foundation for advancing emotion-centered analysis and creation in modern Korean poetry.
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