Articles By

David M. Rothschild

Addendum to: Research note: Examining potential bias in large-scale censored data

Jennifer Allen, Markus Mobius, David M. Rothschild and Duncan J. Watts

Addendum to HKS Misinformation Review “Research note: Examining potential bias in large-scale censored data” (https://doi.org/10.37016/mr-2020-74), published on July 26, 2021.

By Jennifer Allen

Sloan School of Management, Massachusetts Institute of Technology, USA

Markus Mobius

Microsoft Research, USA

David M. Rothschild

Microsoft Research, USA

Duncan J.
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Research Note

Research note: Examining potential bias in large-scale censored data

Jennifer Allen, Markus Mobius, David M. Rothschild and Duncan J. Watts

We examine potential bias in Facebook’s 10-trillion cell URLs dataset, consisting of URLs shared on its platform and their engagement metrics. Despite the unprecedented size of the dataset, it was altered to protect user privacy in two ways: 1) by adding differentially private noise to engagement counts, and 2) by censoring the data with a 100-public-share threshold for a URL’s inclusion.

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