Published inUnderstanding RecommendersExperiments are the Best Kind of Transparency— Luke Thorburn, Jonathan Stray, Priyanjana BenganiJun 9, 2024Jun 9, 2024
Published inUnderstanding RecommendersWhat’s the Difference Between Search and Recommendation?— Luke Thorburn, Jonathan Stray, Priyanjana BenganiOct 25, 20232Oct 25, 20232
Published inUnderstanding RecommendersMaking Amplification Measurable— Luke Thorburn, Jonathan Stray, Priyanjana BenganiMay 7, 2023May 7, 2023
Published inUnderstanding RecommendersWhen You Hear “Filter Bubble”, “Echo Chamber”, or “Rabbit Hole” — Think “Feedback Loop”— Luke Thorburn, Jonathan Stray, Priyanjana BenganiMar 30, 20231Mar 30, 20231
Published inUnderstanding RecommendersIs Optimizing for Engagement Changing Us?— Luke Thorburn, Jonathan Stray, Priyanjana BenganiOct 10, 2022Oct 10, 2022
Published inUnderstanding RecommendersHow to Measure the Causal Effects of RecommendersThe capabilities researchers need to understand how much societal harm is caused by recommender systems on social media.Jul 20, 20221Jul 20, 20221
Published inUnderstanding RecommendersWhat Will “Amplification” Mean in Court?— Luke Thorburn, Jonathan Stray, Priyanjana BenganiMay 23, 2022May 23, 2022
Published inUnderstanding RecommendersWhat Does it Mean to Give Someone What They Want? The Nature of Preferences in Recommender Systems— Luke Thorburn, Jonathan Stray, Priyanjana BenganiMar 11, 20221Mar 11, 20221
Published inUnderstanding RecommendersHow Platform Recommenders WorkA recommender system (or simply ‘recommender’) is an algorithm that takes a large set of items and determines which of those to display to…Jan 20, 2022Jan 20, 2022
