Practical overview
When it fits
Use it when you need a research-oriented starting point for collecting IMDb review data and quantifying its sentiment with an asynchronous GPT-4o workflow.
Who it is for
- Researchers studying sentiment in unstructured review text and its relationship to financial-market attention.
- Developers and analysts exploring a Python and Jupyter-based review collection and GPT-4o scoring workflow.
Documented uses
- Discover movie URLs and collect review text and movie metadata.
- Clean review text and process it through GPT-4o for structured sentiment scores.
- Prepare review-sentiment measures for research on investor attention distraction.
Requirements & limits
The repository is public and marked with an MIT license. The documented sentiment-quantification pipeline requires an OpenAI API key.
- The project is documented as Python 3.9+ code with a Jupyter Notebook analysis stage.
- Review collection and GPT-4o sentiment analysis are separate documented stages.
- The README describes asynchronous OpenAI processing and Pydantic schema validation for sentiment outputs.
- The README reports a research corpus of more than 247,000 IMDb reviews from 2000–2024; this is a reported study result, not a promise about future collection.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up the review-analysis repository
Prepare the documented Python environment and credentials for the sentiment-quantification workflow.
Before you start
- Python 3.9 or later
- An OpenAI API key for the sentiment quantification pipeline
- Repository files, including requirements.txt
Steps
Clone the repository using its documented GitHub URL.
Install the dependencies with pip install -r requirements.txt.
Create a .env file in the repository root and place the key in an OPENAI_API_KEY entry.
Open notebooks/01_sentiment_pipeline.ipynb with Jupyter Notebook for the documented asynchronous analysis workflow.
Expected outcome
A configured environment with the project notebook available for the GPT-4o sentiment-analysis stage.
Guide limitations
- An OpenAI API key is required for sentiment quantification.
- The README documents setup and notebook use; this guide does not establish that the pipeline has been executed or that a particular run will succeed.
Start the documented review-collection stage
Initiate the repository’s documented IMDb review collection step.
Before you start
- The repository cloned locally
- Python 3.9 or later
- Dependencies installed from requirements.txt
Steps
Run python src/acquisition/03_collect_reviews.py from the repository.
Continue to the sentiment-quantification stage through notebooks/01_sentiment_pipeline.ipynb, as described in the README.
Expected outcome
The README-directed collection stage is initiated, with the notebook identified as the next analysis stage.
Guide limitations
- Sentiment quantification requires an OpenAI API key.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 14 October 2026
- Original website title
- WLXie-Tony/Movie_Review_Analysis · Official homepage title · retained in its source language