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Differential Privacy + Wikipedia Exploration

No guarantees are made that this tool will be maintained.

This is an experimental tool hosted on Toolforge. No additional personal data is collected by this tool per the Cloud Services Terms of Use.

This tool showcases how different approaches to differential privacy might affect top-viewed lists. In reality, this approach would likely be applied to e.g., pageviews by country, but here we use the top-viewed articles in a wiki (public data) as a proxy.

Top-viewed Articles on a Wikipedia

This tool fetches the top-viewed articles for a given wiki from yesterday. First you have the actual data -- i.e. accurate counts without any noise added. Then you have the data after differential privacy (DP) has been applied (specifically noise drawn from a Laplace distribution).

You can play around with the different hyperparameters to see how it affects the results. See this Facebook blogpost for a good worked example.

Language code: which Wikipedia language to query -- e.g., en for English Wikipedia.

Epsilon (ε): privacy parameter. Default to 1 but the smaller you make it, the more privacy-preserving.

Sensitivity: the maximum amount that any individual can add to the result. For example, if this is daily user pageviews, 800 would be appropriate as IP+UA hashes that are associated with more than 800 pageviews in a day are labeled as "automated".