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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- ko |
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tags: |
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- emotion |
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- classification |
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- digitalhumanities |
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size_categories: |
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- 1K<n<10K |
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--- |
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### KPoEM (Korean Poetry Emotion Mapping) Dataset |
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We collected **483 poems from five prominent Korean modern poets**: Kim So-wol (165 poems), Yun Dong-ju (113 poems), Im Hwa (44 poems), Yi Sang (47 poems), and Han Yong-un (118 poems). We scraped their major works from public domain sources, including "Azaleas" (Korean: 진달래꽃, Jindallaekkot), "Sky, Wind, Stars, and Poetry" (Korean: 하늘과 바람과 별과 시, Haneulgwa baramgwa byeolgwa si), "Hyunhaetan" (Korean: 현해탄, Hyeonhaetan; Hanja: 玄海灘) , "Silence of My Beloved" (Korean: 님의 침묵, Nimui chimmuk), In the case of Yi Sang, the dataset focuses on his Korean-language series poems such as "Crow's Eye View" (Korean: 오감도, Ogamdo; Hanja: 烏瞰圖), "Reverse" (Korean: 역단, Yeokdan; Hanja: 易斷), and "Critical Condition" (Korean: 위독, Widok; Hanja: 危篤). |
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In results, this dataset has a total of **7,007 emotion-annotated line-level text**. |
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In v4, the names of some columns that were originally in Korean were changed to English. |
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- **Prerprint Paper**: [Decoding the Poetic Language of Emotion in Korean Modern Poetry: Insights from a Human-Labeled Dataset and AI Modeling](https://doi.org/10.48550/arXiv.2509.03932) |
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### KPoEM 데이터셋 사용 안내 |
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본 저장소에는 두 가지 데이터셋이 포함되어 있습니다. |
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- KPoEM_line_dataset_v4.tsv : 시 행 단위(line-level) 데이터셋 |
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- KPoEM_poem_dataset_v4.tsv : 시 작품 단위(poem-level) 데이터셋 |
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⚠️ 주의: 두 데이터셋의 컬럼 구조가 달라서 datasets.load_dataset()으로 동시에 불러올 경우 CastError가 발생합니다. 따라서 개별 파일을 pandas DataFrame으로 로드 후 필요에 맞게 편집하는 방식을 권장합니다. |
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1️⃣ 행 단위(Line-level) 데이터 불러오기 예시 |
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<pre markdown="1"> |
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from datasets import load_dataset |
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df_line = load_dataset( |
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"csv", |
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data_files={ "train": "hf://datasets/AKS-DHLAB/KPoEM/KPoEM_line_dataset_v4.tsv"}, |
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delimiter="\t", |
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encoding="utf-8", |
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quoting=3, |
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) |
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df = df_line["train"].to_pandas() |
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df.head() |
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</pre> |
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2️⃣ 작품 단위(Poem-level) 데이터 불러오기 예시 |
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<pre markdown="2"> |
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from datasets import load_dataset |
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df_poem = load_dataset( |
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"csv", |
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data_files={ |
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"train": "hf://datasets/AKS-DHLAB/KPoEM/KPoEM_poem_dataset_v4.tsv"}, |
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delimiter="\t", |
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encoding="utf-8", |
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quoting=3, |
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) |
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df = df_poem["train"].to_pandas() |
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df.head() |
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</pre> |
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### Contributors |
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- **IRO LIM** — Producer, Dataset Lead |
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- **Haein Ji** — Data Curator |
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- **Sul Koo** — Annotator |
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- **Song-yi Jung** — Annotator |
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- **Jonghoon Yun** — Annotator |
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- **Byungjun Kim** — Supervisor |
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*** |
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- Please refer to the following presentation: LIM, I., Ji, H., & Kim, B. (2025). 한국 근현대시 감정 라벨링 데이터셋 구축: 문학 텍스트의 컴퓨터 기반 감정 분류와 생성형 AI 활용을 위한 기초 연구. 제2회 한국현대문학자대회 (KorLitConf), Seoul, Korea. Zenodo. [https://doi.org/10.5281/zenodo.15055795](https://doi.org/10.5281/zenodo.15055795) |
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- All source code used in this study has been made publicly available in the following repository. See the link for details. [https://github.com/AKS-DHLAB/KPoEM](https://github.com/AKS-DHLAB/KPoEM) |
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- train, validation, test dataset **구분 없이** 문장(line) 단위, 작품(poem) 단위 tsv 파일로 업로드하였습니다. |
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- Update Records: The KPoEM dataset has been updated and is permanently archived on Zenodo. [DOI: KPoEM dataset v4.0 in zenodo](https://doi.org/10.5281/zenodo.15598092) |
