U.S. Broadband Coverage Data Set: A Differentially Private Data Release
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Abstract (arXiv)
Broadband connectivity is a key metric in today's economy. In an era of rapid expansion of the digital economy, it directly impacts GDP. Furthermore, with the COVID-19 guidelines of social distancing, internet connectivity became necessary to everyday activities such as work, learning, and staying in touch with family and friends. This paper introduces a publicly available U.S. Broadband Coverage data set that reports broadband coverage percentages at a zip code-level. We also explain how we used differential privacy to guarantee that the privacy of individual households is preserved. Our data set also contains error ranges estimates, providing information on the expected error introduced by differential privacy per zip code. We describe our error range calculation method and show that this additional data metric does not induce any privacy losses.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Mar 2021.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 4.
5 papers.
- 2023Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Datacited by 8
- 2021An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprisescited by 6
- 2023Samplable Anonymous Aggregation for Private Federated Data Analysiscited by 6
- 2023SpaCE: The Spatial Confounding Environmentcited by 3
- 2023Differential Privacy via Distributionally Robust Optimizationcited by 2
- 2023SpaCE: The Spatial Confounding Environment1 Dec 2023
- 2023Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Data30 Oct 2023
- 2023Samplable Anonymous Aggregation for Private Federated Data Analysis27 Jul 2023
- 2023Differential Privacy via Distributionally Robust Optimization25 Apr 2023
- 2021An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises15 Jun 2021