Researcher ORCID Identifier
0009-0002-7298-9981
Graduation Year
2024
Date of Submission
12-2024
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
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Second Department
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Reader 1
Mark Huber
Terms of Use & License Information
Rights Information
© 2024 Sarah Jane S Fullerton
Abstract
This research investigates the historical trends of psychological distress in the U.S. in relation to natural disaster occurrences. By analyzing long-term data, we examine how significant natural disasters relate to levels of psychological distress over time. The research employs Exploratory Data Analysis (EDA) and Time Series Analysis to identify patterns and trends between the frequency and intensity of natural disasters and the rise of psychological distress across various periods in U.S. history. Additionally, real-time data from Reddit was collected through a custom-built Reddit web scraper specialized for Hurricane Helene. This dataset was labeled for sentiment and used to train machine learning models for sentiment analysis, providing valuable tools for understanding emotional responses in real-time. Their adaptability makes them applicable for future use in crisis response. The findings of this research offer a dual perspective: understanding the broader historical relationship between natural disasters and psychological distress, and providing insights into emotional reactions to 2024 events.
Recommended Citation
Fullerton, Sarah Jane, "Exploring U.S. Natural Disasters and Psychological Distress: From Time Series Trends to Machine Learning Insights on Hurricane Helene" (2024). CMC Senior Theses. 3756.
https://scholarship.claremont.edu/cmc_theses/3756
Data Repository Link
https://github.com/sjanefullerton/time-series
https://github.com/sjanefullerton/Web-Scraper
https://github.com/sjanefullerton/Sentiment-Analysis