14 citations · 52 across the 10 of their papers we have counts for
10 papers
Measuring risks inherent to our digital economies using Amazon purchase histories from US consumers
Alex Berke, Kent Larson, Sandy Pentland +1
What do pickles and trampolines have in common? In this paper we show that while purchases for these products may seem innocuous, they risk revealing clues about customers' persona…
Evaluating Amazon Effects and the Limited Impact of COVID-19 With Purchases Crowdsourced from US Consumers
Alex Berke, Dana Calacci, Alex +2
We leverage a recently published dataset of Amazon purchase histories, crowdsourced from thousands of US consumers, to study how online purchasing behaviors have changed over time,…
Insights from an experiment crowdsourcing data from thousands of US Amazon users: The importance of transparency, money, and data use
Alex Berke, Robert Mahari, Sandy Pentland +2
Data generated by users on digital platforms are a crucial resource for advocates and researchers interested in uncovering digital inequities, auditing algorithms, and understandin…
Privacy Limitations Of Interest-based Advertising On The Web: A Post-mortem Empirical Analysis Of Google's FLoC
Alex Berke, Dan Calacci
In 2020, Google announced it would disable third-party cookies in the Chrome browser to improve user privacy. In order to continue to enable interest-based advertising while mitiga…
The tradeoff between the utility and risk of location data and implications for public good
Dana Calacci, Alex Berke, Kent Larson +2
High-resolution individual geolocation data passively collected from mobile phones is increasingly sold in private markets and shared with researchers. This data poses significant…
Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning
Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey +4
A common technique to improve learning performance in deep reinforcement learning (DRL) and many other machine learning algorithms is to run multiple learning agents in parallel. A…