Nearly every aspect of modern life has become a data-generating event, with many activities leaving behind traces as byproducts that are logged by platforms or devices. These trace data offer researchers powerful tools for studying communication, enabling greater granularity and specificity, real-time and in-situ collection, and reduced reliance on self-report or perceptual judgment. However, these benefits are accompanied by significant challenges, including biases in data sources, ethical concerns related to privacy and consent, methodological hurdles in data collection and analysis, and possible (mis)matches between observable constructs in traces and those that are theoretically interesting. This chapter provides a foundational overview of trace data in communication research. It systematizes trace data by distinguishing traces as either 1) usage logs or 2) sensor readings. Usage logs are further characterized along platform vs. device sources and content vs. metadata dimensions. Sensor data are classified as either contextual or physiological, and as continuous or episodic in temporal resolution. For these traces, the chapter discusses data sources, collection methods, and associated opportunities and limitations. Alongside these methodological aspects, the chapter emphasizes the importance of theoretical grounding in guiding the use and interpretation of trace data in communication research.
Parry et al. (Tue,) studied this question.