Research note: Examining potential bias in large-scale censored data
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 co...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Harvard Kennedy School
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/80016e4f3a1e416fb698034437bd6baa |
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