Studying Preferences and Concerns about Information Disclosure in Email Notifications

TL;DR

This study investigates how often email notifications cause accidental information disclosures and examines user preferences and concerns, using surveys and labeling studies, to inform the design of privacy-aware notification systems.

Contribution

It provides empirical data on disclosure risks and introduces machine learning methods to predict user comfort with notifications based on context.

Findings

53% of users face at least 10% risk of disclosure from email notifications

User concerns vary with meeting and email attributes such as recipients and attendees

Machine learning models can predict user comfort levels with notifications

Abstract

The proliferation of network-connected devices and applications has resulted in people receiving dozens, or hundreds, of notifications per day. When people are in the presence of others, each notification poses some risk of accidental information disclosure; onlookers may see notifications appear above the lock screen of a mobile phone, on the periphery of a desktop or laptop display, or projected onscreen during a presentation. In this paper, we quantify the prevalence of these accidental disclosures in the context of email notifications, and we study people's relevant preferences and concerns. Our results are compiled from an exploratory retrospective survey of 131 respondents, and a separate contextual-labeling study in which 169 participants labeled 1,040 meeting-email pairs. We find that, for 53% of people, at least 1 in 10 email notifications poses an information disclosure risk. We also find that the real or perceived severity of these risks depend both on user characteristics and attributes of the meeting or email (e.g. the number of recipients or attendees). We conclude by exploring machine learning algorithms to predict people's comfort levels given an email notification and a context, then we present implications for the design of future contextually-relevant notification systems.