Interference and spillover effects in recommendation surfaces
Causal Inference
Interference
Spillovers
Recommendation Systems
A project studying how promoting one item affects both that item and nearby competing items when recommendation units interfere.
Decision Question
How does promoting one item affect both that item and nearby competing items in the recommendation surface?
Causal Setup
- Treatment: focal item promotion in simulated recommendation slates.
- Outcomes: direct item response plus nearby-item displacement or spillover response.
- Challenge: standard no-interference assumptions do not hold.
Methods
- Spillover exposure mapping
- Cluster-randomized estimators
- Direct, indirect, and total effects
- Advanced spillover models
- Sensitivity and final reporting
Portfolio Takeaway
The project makes the portfolio signal that causal claims in ranking and marketplaces must account for displacement, spillovers, and constrained attention.
Selected Figures
Notebook Sequence
The links below open rendered HTML versions of the notebooks. The source .ipynb files are kept in the matching folder under notebooks/projects/.
Generated Artifacts
Limitations
These are notebook-driven causal analyses, not production guarantees. Each project should be read with its identification assumptions, support diagnostics, measurement choices, and sensitivity checks in view.