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Exploring Changes in Sense of Place Post-Events Using Large Language Models

Domain:

natural language processing

Record type:

paper
Creator:
Karimi, MinaMajic, IvanJanowicz, Krzysztof
Publisher:
Zenodo
Host:avatar

This paper explores the temporal evolution of the sense ofplace (SoP) in diverse global destinations before and after significantevents, in order to understand the complex interplay between societalperceptions and transformative occurrences. Examining places such asHiroshima, Chernobyl, South Africa, Paris, and Wuhan, and the eventsthat took place there such as atomic bombing, nuclear disaster, FIFAWorld Cup, terrorist attacks, and pandemics, we employ Large LanguageModels (LLMs) analysis to obtain insights into the shifting dynamics ofSoP. Acknowledging the shortage of systematic research in this domain,our study explores the effects of important events on individual’s sentimentsand behaviors. By examining specific case studies, we aim to providea detailed understanding of the evolving SoP and its implications,offering a foundation for future scholarship and strategic considerationsin the realms of academia, policy, and industry.

Visit

doi.org

Tags

Sense of Place (SoP)Large Language ModelsChatGPTSentiment AnalysisTemporal Variation

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode