Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0)
This provides a publicly accessible dataset for researchers studying COVID-19 symptoms via search trends, with privacy guarantees, but it is incremental as it focuses on process description rather than new methods or results.
The paper describes the aggregation and anonymization process for the COVID-19 Search Trends symptoms dataset, which uses differential privacy with ε = 1.68 to protect user search activity while making the data publicly available.
This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19symptomdataset on September 2, 2020), a publicly available dataset that shows aggregated, anonymized trends in Google searches for symptoms (and some related topics). The anonymization process is designed to protect the daily symptom search activity of every user with $\varepsilon$-differential privacy for $\varepsilon$ = 1.68.