| Budget Amount *help |
¥15,730,000 (Direct Cost: ¥12,100,000、Indirect Cost: ¥3,630,000)
Fiscal Year 2021: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2020: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2019: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2018: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
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| Outline of Final Research Achievements |
In this study, we applied machine learning-based natural language processing techniques, notably topic modeling and word embedding, to analyze a corpus of Late Modern English novels, thereby proposing a new model for corpus stylistics research. This approach has illuminated topics and groups of words composed of low-frequency occurrences that traditional corpus linguistics methods might overlook, offering a quantitative foothold for exploring 'issues of meaning' that were previously difficult to approach with conventional methods. Based on the methodologies and insights derived from this research, we have initiated the formation of a collaborative foundation aimed at constructing a large-scale international research network with our academic partners both domestically and abroad.
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