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Peoples' activities and opinions recorded as digital traces online,especially on social media and other web-based platforms, offer increasinglyinformative pictures of the public. They promise to allow inferences aboutpopulations beyond the users of the platforms on which the traces are recorded,representing real potential for the Social Sciences and a complement tosurvey-based research. But the use of digital traces brings its owncomplexities and new error sources to the research enterprise. Recently,researchers have begun to discuss the errors that can occur when digital tracesare used to learn about humans and social phenomena. This article synthesizesthis discussion and proposes a systematic way to categorize potential errors,inspired by the Total Survey Error (TSE) Framework developed for surveymethodology. We introduce a conceptual framework to diagnose, understand, anddocument errors that may occur in studies based on such digital traces. Whilethere are clear parallels to the well-known error sources in the TSE framework,the new "Total Error Framework for Digital Traces of Human Behavior on OnlinePlatforms" (TED-On) identifies several types of error that are specific to theuse of digital traces. By providing a standard vocabulary to describe theseerrors, the proposed framework is intended to advance communication andresearch concerning the use of digital traces in scientific social research.

TED-On: A Total Error Framework for Digital Traces of Human Behavior on Online Platforms