An Experimental Study of Structural Diversity in Social Networks
Jessica Su, Krishna Kamath, Aneesh Sharma, Johan Ugander, Sharad Goel

TL;DR
This study experimentally investigates whether structural diversity in social networks causally affects user retention, finding that artificially varying diversity levels does not significantly impact retention rates, thus challenging previous observational correlations.
Contribution
It provides the first large-scale randomized controlled experiment to test the causal effect of structural diversity on social network user retention.
Findings
Structural diversity correlates with retention in observational data.
Manipulating structural diversity does not significantly change retention.
Challenges the causal interpretation of previous observational studies.
Abstract
Several recent studies of online social networking platforms have found that adoption rates and engagement levels are positively correlated with structural diversity, the degree of heterogeneity among an individual's contacts as measured by network ties. One common theory for this observation is that structural diversity increases utility, in part because there is value to interacting with people from different network components on the same platform. While compelling, evidence for this causal theory comes from observational studies, making it difficult to rule out non-causal explanations. We investigate the role of structural diversity on retention by conducting a large-scale randomized controlled study on the Twitter platform. We first show that structural diversity correlates with user retention on Twitter, corroborating results from past observational studies. We then exogenously…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSocial Media and Politics · Opinion Dynamics and Social Influence · Social Capital and Networks
