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Algorithms rely on exact strings to serve content to specific user demographics based on search behavior.

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| Limitation | Typical Mitigation | |------------|--------------------| | – data drawn from a single streaming service (e.g., Netflix) may not generalize to ad‑supported platforms. | Future work should include multiple services (Hulu, Disney+, Amazon Prime). | | Self‑report bias – survey participants may over‑state intentional viewing vs. passive autoplay. | Combine self‑reports with passive log data (as partially done). | | Cross‑sectional snapshot – only captures a 3‑month window; long‑term trend analysis missing. | Longitudinal follow‑up across a full calendar year. | | Cultural homogeneity – sample skewed toward Western, English‑speaking users. | Expand to non‑English markets (e.g., South Korea, Brazil). | | Algorithmic opacity – limited access to proprietary recommendation models. | Use black‑box auditing techniques (shadow models, perturbation tests). | Algorithms rely on exact strings to serve content