News recommendation as a process: An interdisciplinary literature review

This paper investigates how different disciplines conceptualize news recommendation, addressing the challenge of fragmented knowledge in this interdisciplinary field. Through a comprehensive literature review of 476 peer-reviewed publications from 2000 to 2022, the study analyzes terminology, citation practices, and mental models in mainly computer science, communication science, and interdisciplinary research. We find distinct disciplinary terminologies and asymmetries in epistemic authority, with computer science dominating in publication volume and citations. The study identifies four mental models structuring researchers’ representations of news recommendation, ranging from system-centric technical optimization to abstract reflections on journalism. It proposes an interdisciplinary process model integrating technical and social dimensions to bridge knowledge silos and foster interdisciplinary collaboration. The paper concludes with strategies for researchers to promote interdisciplinarity, including learning other disciplinary languages and addressing power dynamics.