People suffer from information overload while using digital devices, yet little is known about the interaction of the overload experiences and everyday web behavior. We conducted a large-scale longitudinal observational study (N=277) over seven months. The study combines over 13M passively observed web traces from desktop computers and mobile devices with four waves of surveys measuring the experienced information overload. Our results demonstrate that repetitive, short-duration use of devices (i.e., high sparseness) in online sessions differentiate highly overloaded individuals from others with a large effect. Furthermore, mobile web duration and session sparseness predict increase in the overload. Overall, our results highlight that the web usage duration, the temporal patterns of usage, and the choice of a device are associated with information overload. By highlighting session sparseness as an actionable behavioral signal, our results inform the development of digital well-being tools that nudge users toward healthier interaction patterns and reduce overload.

Everyone needs to somehow manage personal information, and there are numerous choices for technologies that support personal information management (PIM). Meanwhile, many suffer from experiences of information overload related to PIM. We developed a quantitative model of information overload in PIM and tested it against data we collected in a large-scale survey study (N = 1,011). Using structural equation modeling, we found that using many PIM technologies accounts for information overload through practices of keeping information and feeling of desperation, and through organizing and feeling of efficacy, but not directly. Our study deepens the understanding of information overload in the context of PIM and distinguishes different roles that technologies, practices, and affects have in relation to it. The findings highlight how designs and interventions targeted to reduce negative affects related to PIM could be the most effective in countering information overload.

In this paper, we investigate browsing clutter, which refers to cluttered experiences of users due to buildup of disorganized browser elements and information. We studied what users experience as clutter, what behaviors and factors contribute to the clutter, and what users do when they experience clutter through an interview study (N = 16) and an online survey study (N = 400). Based on our studies, browsing clutter includes the amount of tabs and windows, content of the web pages and interactive elements, navigation, and search process. We identified sources of browsing clutter from task characteristics, such as importance and complexity, to user habits, such as multitasking and tab closing. To reveal the dynamics of browsing clutter, we modeled how browsing clutter is predicted by specific browsing habits and coping strategies. Our model demonstrates how individual forms of clutter are interrelated and altered by behavior. We discuss how browsing clutter relates to information overload.