WLXie-Tony/Movie_Review_Analysis
Official replication package for IJFE (2026). Asynchronous ETL pipeline using GPT-4o to quantify investor distraction shocks from unstructured movie reviews.
This project helps financial researchers and economists quantify investor attention shocks by analyzing large volumes of unstructured movie reviews. It takes raw IMDb movie review text and metadata as input and produces a high-frequency sentiment index, which can then be used to test hypotheses about financial market behavior. The primary users are quantitative finance researchers, academics, and financial analysts interested in alternative data sources for market insights.
154 stars.
Use this if you need to systematically extract and quantify sentiment from a large corpus of unstructured text, especially for financial market analysis or academic research.
Not ideal if you're looking for a simple, off-the-shelf movie recommendation system or a general-purpose sentiment analysis tool for casual use.
Stars
154
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 16, 2026
Commits (30d)
0
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