Behavioral logs are traces of human behavior seen through the lenses of sensors that capture and record user activity. They include behavior ranging from low-level keystrokes to rich audio and video recordings. Traces of behavior have been gathered in psychology studies since the 1930s (Skinner, 1938 ), and with the advent of computerbased applications it became common practice to capture a variety of interaction behaviors and save them to log fi les for later analysis. In recent years, the rise of centralized, web-based computing has made it possible to capture human interactions with web services on a scale previously unimaginable. Largescale log data has enabled HCI researchers to observe how information diffuses through social networks in near real-time during crisis situations (Starbird & Palen, 2010 ), characterize how people revisit web pages over time (Adar, Teevan, & Dumais, 2008 ), and compare how different interfaces for supporting email organization infl uence initial uptake and sustained use (Dumais, Cutrell, Cadiz, Jancke, Sarin, & Robbins, 2003 ; Rodden & Leggett, 2010 ). In this chapter we provide an overview of behavioral log use in HCI. We highlight what can be learned from logs that capture people’s interactions with existing computer systems and from experiments that compare new, alternative systems. We describe how to design and analyze web experiments, and how to collect, clean and use log data responsibly. The goal of this chapter is to enable the reader to design log studies and to understand results from log studies that they read about. Understanding User Behavior Through Log Data and Analysis