Abstract
By using computational techniques to analyze literature, deeper insights can be gained into human-water relationships across different historical and cultural contexts. Natural Language Processing (NLP) and other data science methods can explore applications of traditional ecological knowledge (TEK) and underlying emotions or beliefs in literature to help understand sustainability. Protecting this sensitive cultural data through ethical applications can further secure future implementations of policies, urban planning, and environmental relationships.
Faculty Advisor/Mentor
Iria Giuffrida
Document Type
Paper
Disciplines
Cybersecurity | Databases and Information Systems | Data Science | Digital Humanities | Environmental Health and Protection | Information Security | Sustainability
DOI
10.25776/6jsv-k976
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Included in
Cybersecurity Commons, Databases and Information Systems Commons, Data Science Commons, Digital Humanities Commons, Environmental Health and Protection Commons, Information Security Commons, Sustainability Commons
Digital Humanities: Using Computational Methods on Literature to Understand Human-Water Relations
By using computational techniques to analyze literature, deeper insights can be gained into human-water relationships across different historical and cultural contexts. Natural Language Processing (NLP) and other data science methods can explore applications of traditional ecological knowledge (TEK) and underlying emotions or beliefs in literature to help understand sustainability. Protecting this sensitive cultural data through ethical applications can further secure future implementations of policies, urban planning, and environmental relationships.