| 研究課題/領域番号 |
22K18154
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分90020:図書館情報学および人文社会情報学関連
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| 研究機関 | 早稲田大学 |
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研究代表者 |
OHMAN Emily 早稲田大学, 国際学術院, 講師(テニュアトラック) (60906543)
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| 研究期間 (年度) |
2022-04-01 – 2024-03-31
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| 研究課題ステータス |
交付 (2022年度)
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| 配分額 *注記 |
1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
2023年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
2022年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
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| キーワード | sentiment analysis / CLS / emotion detection / NLP / machine learning / word embeddings / affect studies |
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| 研究開始時の研究の概要 |
With the creation of period- and genre-specific language models for turn-of-the-century literary texts this project aims to deliver robust tone and mood detection methods for literary studies that will not only improve existing computational literary studies approaches, but also sentiment analysis.
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| 研究実績の概要 |
I have developed emotion lexicons for emotion association and emotion intensity. These lexicons were used to create affective word embeddings from an initial corpus of 1000 works of literature. In an iterative process, the lexicons can then be enhanced and expanded and used to fine-tune the emotion detection model for the specific domain and to adjust for semantic shifts in language. We have been able to show that mood can quite accurately be detected computationally by focusing on the first three paragraphs of a book. A by-product of this project was the development of a Finnish chapterize package that splits these books into chapters automatically.
The findings were disseminated in two peer-reviewed papers and presented at several international conferences. Three more papers are currently in peer-review. Both the lexicons and the literature corpus have been made publicly available.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
I was able to discover a method for mood detection and publish about it already, which left time to explore other uses of the same methodology resulting in new international collaborations. The project scope has therefore been expanded slightly to include fractal sentiment arcs in literature.
Research output has also exceeded expectations with two papers already published and three more currently in peer-review. Only two papers were anticipated this fiscal year.
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| 今後の研究の推進方策 |
We plan on exploring both phonoemotions (the emotion associations of certain sounds) in the corpus as well as fractal sentiment arcs in conjunction with the methodology developed for this project. I will also work on further improving the current emotion model by incorporating and fine-tuning large language models.
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