Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description

Akim Kumok; Alex Fabrikant; Andrew Mingbo Dai; Chaitanya Kamath; Charlotte Stanton; Damien Desfontaines; Dennis Kraft; Evgeniy Gabrilovich; Gerardo Flores; Gregory Alexander Wellenius; Ilya Eckstein; Irippuge Milinda Perera; Izhak Shafran; John S. Davis; Karthik Raman; Katie Everett; Krishna Kumar Gadepalli; Masrour Zoghi; Mimi Sun; Rayman Huang; Shailesh Bavadekar; Thomas Ludwig Roessler; Venky Ramachandran; Yael Mayer

Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description

Akim Kumok
Alex Fabrikant
Andrew Mingbo Dai
Chaitanya Kamath
Charlotte Stanton
Damien Desfontaines
Dennis Kraft
Evgeniy Gabrilovich
Gerardo Flores
Gregory Alexander Wellenius
Ilya Eckstein
Irippuge Milinda Perera
Izhak Shafran
John S. Davis
Karthik Raman
Katie Everett
Krishna Kumar Gadepalli
Masrour Zoghi
Mimi Sun
Rayman Huang
Shailesh Bavadekar
Thomas Ludwig Roessler
Venky Ramachandran
Yael Mayer

Arxiv.org, N/A (2020)

Abstract

This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset, 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 search activity of every user with \varepsilon-differential privacy for \varepsilon = 1.68.

Research Areas

Health & Bioscience

Security, Privacy and Abuse Prevention

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