텍스트 마이닝을 활용한 기후변화 내러티브 분석: 닐 셔스터먼과 재러드 셔스터먼의 『드라이』와 J.G. 발라드의『가뭄』비교 연구

Text Mining-Based Analysis of Climate Change Narratives: A Comparative Study of Neal Shusterman and Jarrod Shusterman's Dry and J.G. Ballard's The Drought

This study applies text mining methodologies—LDA topic modeling, K-means clustering, and AFINN sentiment analysis—to comparatively analyze Neal Shusterman and Jarrod Shusterman's Dry (2018) and J. G. Ballard's The Drought (1964). Dry emphasizes infrastructure collapse and solidarity formation among young survivors, reflecting adaptive optimism, while The Drought portrays existential paralysis and emotional numbing. Drawing on Bateson's cultural ecology and Clayton's climate psychology, this study demonstrates that both novels reveal climate change as experienced through embodied existence and transformed social relationships. The text mining approach complements traditional literary analysis by objectively identifying thematic patterns. This analysis illuminates how climate fiction has evolved over the past half-century.