The Effect of Recommendations on Network Structure

By Jessica Su, Aneesh Sharma, Sharad Goel. 2016

96 citations recorded by the source corpus.

Subfields: Communication, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Communication

1. Barbara E. Engelhardt
2. Allison June-Barlow Chaney
3. Brandon M Stewart

In Statistical and Nonlinear Physics

1. Prabhakar Raghavan
2. Alessandro Panconesi
3. Barbara E. Engelhardt
4. Allison June-Barlow Chaney
5. Brandon M Stewart
6. Mark Newman

Citations in the corpus

• How algorithmic confounding in recommendation systems increases homogeneity and decreases utility (2017, background): “Some work has also been done to understand the causal impact of these systems on behavior by nding natural experiments in observational data [53, 55] (approximating expensive controlled experiments [33]), but it is unclear howwell these results generalize.”
• The Limits of Popularity-Based Recommendations, and the Role of Social Ties (2016, background): “A study of friend recommendation in Twitter, [28], shows that recommendations of popular users are much more likely to be accepted than recommendations of “average” users.”