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Do algorithmic information environments mark the end of media effects research?

Year: 2026

Type: article

Abstract: Algorithmically curated information environments are beginning to challenge both long-standing notions of what media effects look like and our ability to study them directly. Algorithmic curation and microtargeting of content based on users’ behavioral and digital trace data pose conceptual as well as methodological challenges to our understanding of communication effects. These challenges increasingly introduce significant distortions to our field’s current ability to transparently and systematically iterate between theory and empirical testing. In this article, we provide a blueprint for how a systematic, empirical rethinking, and testing of communication effects theory can look like in an era of what we call preference-based information ecologies (PBIEs). Specifically, we discuss 9 current challenges to theorizing that are conceptual and methodological in nature and discuss necessary field developments to address and overcome these challenges. We identify 4 major agenda items that our field must tackle in order to position itself for a future in which all communication processes occur in some variant of PBIEs.

Source: Annals of the International Communication Association

DOI: 10.1093/anncom/wlag042

Authors: Isabelle Freiling, Jakob Ohme, Isabel I Villanueva, Dietram A Scheufele

Institutions: University of Utah, Weizenbaum Institute, University of Miami, Arizona State University

Language: English

Topic: Media Studies and Communication

Subfield: Communication

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,368

Funders: John Templeton Foundation, Wisconsin Alumni Research Foundation