mlsanityData to 14 Oct 2026

Causal inference for social network data

arXiv 1705.08527 ↗First posted 23 May 2017stat.ME math.ST stat.THcited by 31

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Abstract (arXiv)

We describe semiparametric estimation and inference for causal effects using observational data from a single social network. Our asymptotic results are the first to allow for dependence of each observation on a growing number of other units as sample size increases. In addition, while previous methods have implicitly permitted only one of two possible sources of dependence among social network observations, we allow for both dependence due to transmission of information across network ties and for dependence due to latent similarities among nodes sharing ties. We propose new causal effects that are specifically of interest in social network settings, such as interventions on network ties and network structure. We use our methods to reanalyze an influential and controversial study that estimated causal peer effects of obesity using social network data from the Framingham Heart Study; after accounting for network structure we find no evidence for causal peer effects.

Key facts. Cited by 31 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 May 2017.

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Citing papers per year: 2022: 8; 2023: 2; 2024: 8; 2025: 7; 2026: 6.

31 papers.

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  1. 2022Evaluation Methods and Measures for Causal Learning Algorithmscited by 23
  2. 2026EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environmentscited by 20
  3. 2022Learning Individual Treatment Effects under Heterogeneous Interference in Networkscited by 12
  4. 2022Using Embeddings for Causal Estimation of Peer Influence in Social Networkscited by 9
  5. 2022Estimating Social Influence from Observational Datacited by 5
  6. 2023Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influencecited by 5
  7. 2024A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of Povertycited by 5
  8. 2024Graph Machine Learning based Doubly Robust Estimator for Network Causal Effectscited by 4
  9. 2025Double Machine Learning for Causal Inference under Shared-State Interferencecited by 4
  10. 2024Estimating the treatment effect over time under general interference through deep learner integrated TMLEcited by 3
  11. 2025Scalable Policy Maximization Under Network Interferencecited by 3
  12. 2022Network Synthetic Interventions: A Causal Framework for Panel Data Under Network Interferencecited by 2
19 more
  1. 2022Adaptive Sequential Surveillance with Network and Temporal Dependencecited by 2
  2. 2024Asymmetric Graph Error Control with Low Complexity in Causal Banditscited by 2
  3. 2026Causal Evaluation of Membership Inference Attackscited by 2
  4. 2022Treatment Effect Estimation with Observational Network Data using Machine Learningcited by 1
  5. 2022Privacy Aware Experiments without Cookiescited by 1
  6. 2023Contagion Effect Estimation Using Proximal Embeddingscited by 1
  7. 2025Local Interference: Removing Interference Bias in Semi-Parametric Causal Modelscited by 1
  8. 2025Bayesian Estimation of Causal Effects Using Proxies of a Latent Interference Networkcited by 1
  9. 2025Estimating Heterogeneous Causal Effect on Networks via Orthogonal Learningcited by 1
  10. 2026Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Frameworkcited by 1
  11. 2026Efficient Targeted Maximum Likelihood Estimators for Two-Phase Design Problemscited by 1
  12. 2024A/B testing under Interference with Partial Network Informationcited by 0
  13. 2024IntOPE: Off-Policy Evaluation in the Presence of Interferencecited by 0
  14. 2024Towards Optimal Environmental Policies: Policy Learning under Arbitrary Bipartite Network Interferencecited by 0
  15. 2024Network Causal Effect Estimation In Graphical Models Of Contagion And Latent Confoundingcited by 0
  16. 2025Causally Fair Node Classification on Non-IID Graph Datacited by 0
  17. 2025Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferencescited by 0
  18. 2026Nonparametric efficient inference for network quantile causal effects under partial interferencecited by 0
  19. 2026Peer Effects in Signed Networks: Separating Influence Through Positive and Negative Tiescited by 0