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Recommandation Algorithms
Algorithms that suggest content, products, or connections based on user data and behavior. Widely used on social media, streaming, and shopping platforms, they shape what people see and consume — often reinforcing existing preferences, biases, and filter bubbles.
Bibliography
- Arvind Narayanan, Understanding Social Media Recommendation Algorithms, 23-01 Knight First Amend. Inst. (Mar. 9, 2023), https://knightcolumbia.org/content/understanding-social-media-recommendation-algorithms [https://perma.cc/F3NP-FEQX].
- Whittaker, J., Looney, S., Reed, A., & Votta, F. (2021). Recommender systems and the amplification of extremist content. Internet Policy Review, 10(2). https://doi.org/10.14763/2021.2.1565
- Chan, A., Salganik, R., Markelius, A., Pang, C., Rajkumar, N., Krasheninnikov, D., ... & Maharaj, T. (2023, June). Harms from increasingly agentic algorithmic systems. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 651-666).
- Pathak, R., Spezzano, F., & Pera, M. S. (2023). Understanding the contribution of recommendation algorithms on misinformation recommendation and misinformation dissemination on social networks. ACM Transactions on the Web, 17(4), 1-26.
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