Abstract
User-generated content (UGC) is a fundamental source of information for the study of consumer behavior, product development, and to assess the quality of service. The expansion of branded content, published and mixed with “ordinary” UGC on the same online platforms, blurs the notions of which content should be considered for these studies. This contribution draws on the notion of “authenticity” to offer a taxonomy distinguishing “branded” from “organic” content and presents a computational method to detect branded content in UGC.