Research
Academic research and scholarly work from my time at Duke University and beyond.
Judging Books by Their Covers: Reese's Book Club and Contemporary Bookishness
Senior Honors Thesis, Duke University • March 2024
A comprehensive analysis of Reese's Book Club's impact on contemporary literary culture and the middlebrow reading market. This thesis examines how celebrity book clubs shape reading practices, publishing decisions, and cultural perceptions of literature through computational analysis and literary theory.
Key Findings:
- Analyzed patterns in Reese's Book Club selections using digital humanities methods
- Explored the intersection of celebrity culture and literary taste-making
- Examined the role of social media in contemporary book marketing and reader engagement
- Investigated how book clubs influence publishing industry trends and author visibility
Methodology:
This thesis employed a mixed-methods approach combining quantitative data analysis with qualitative literary criticism. The research included computational analysis of book selection patterns, social media engagement metrics, and close reading of selected texts from Reese's Book Club recommendations.
Ethical Consumption Before Capitalism (ECBC)
Bass Connections Research Project, Duke University • 2021-2022
A computational humanities project exploring premodern ethical consumption practices, specifically analyzing the East India Company's monopoly in England from 1660-1714. This interdisciplinary research combines historical analysis with modern data science techniques to understand early patterns of ethical consumption.
Technical Approach:
- Text analysis and pattern recognition on Early English Books Online (EEBO) corpus
- Topic modeling and sentiment analysis of historical documents
- Word embedding techniques for semantic analysis
- Data visualization including scatter plots, word clouds, and statistical graphs
Technologies Used:
Python, Jupyter Notebooks, natural language processing libraries, and statistical analysis tools for processing and analyzing historical text data.