Collected and cleaned crypto-related text data for analysis-ready corpora.
Research Project
Understanding the 2024 Shiba Inu Surges
A behavioral-finance study built with R and NLP methods.
This research examines behavioral patterns in cryptocurrency conversations surrounding the March and November 2024 Shiba Inu rallies. I combined statistical analysis in R with NLP workflows to study how sentiment, themes, and reaction timing moved as market conditions changed.
Method
Built NLP pipelines in R for tokenization, sentiment scoring, and topic signals.
Compared sentiment and narrative shifts across periods of market volatility.
Key Findings
Discussion sentiment moved quickly with price volatility and major news cycles.
Topic clusters exposed recurring behavioral themes during high-uncertainty windows.
NLP-based signals helped surface shifts in market narrative earlier than manual review.