Beyond Optimizing for Clicks: Incorporating Editorial Values in News Recommendation
Feng Lu, Anca Dumitrache, David Graus
Abstract
With the uptake of algorithmic personalization in the news domain, news organizations increasingly trust automated systems with previously considered editorial responsibilities, e.g., prioritizing news to readers. In this paper we study an automated news recommender system in the context of a news organization's editorial values.
Topics & Concepts
PersonalizationComputer scienceContext (archaeology)Recommender systemWorld Wide WebData scienceInformation retrievalInternet privacyNews mediaBig dataFake newsHeadlineRecommender Systems and TechniquesTopic ModelingInformation Retrieval and Search Behavior