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Algorithmic curation of social media platforms is considered to create a clickbait media environment. Although clickbait practices can be risky especially for legacy news outlets, clickbait is widely applied. We conceptualize clickbait content supply as a revision game with an unknown threshold. Combining supervised machine learning with time series analysis of Facebook posts and Twitter messages of 37 German legacy news outlets over 54 months, we observe outlets’ behavior following algorithm changes. Results reveal (1) an infrequent use of clickbait with few heavier-using outlets and (2) turning points of clickbait performance as clickbait supply and user interaction form a reversed U-shaped relationship. News outlets (3) collectively adjust toward an industry clickbait standard. While we (4) cannot prove that algorithmic curation increases clickbait, (5) Facebook’s regulative intervention to decrease clickbait disperses heterogeneous tendencies in clickbait supply. We contribute to an understanding of editorial decision-making in competitive environments facing platforms’ regulative intervention.

News recommender systems are an increasingly popular field of study that attracts a growing interdisciplinary research community. As these systems play an essential role in our daily lives, the mechanisms behind their curation processes are under scrutiny. In the area of personalized news, many platforms make design choices driven by economic incentives. In contrast to such systems that optimize for financial gain, there can be norm-driven diversity systems that prioritize normative and democratic goals. However, their impact on users in terms of inducing behavioral change or influencing knowledge is still understudied. In this paper, we contribute to the field of news recommender system design by conducting a user study that examines the impact of these normative approaches. We a.) operationalize the notion of a deliberative public sphere for news recommendations, show b.) the impact on news usage, and c.) the influence on political knowledge, attitudes and voting behavior. We find that exposure to small parties is associated with an increase in knowledge about their candidates and that intensive news consumption about a party can change the direction of attitudes of readers towards the issues of the party.

Tageszeitungsverlage im deutschsprachigen Raum stehen weiterhin vor großen Herausforderungen die digitale Transformation zu meistern. Dabei müssen die Medienhäuser insbesondere auch den Wandel von einer analogen zu einer digitalen Vertriebsorganisation bewerkstelligen. Die Wahl der Vertriebswege ist eng an die normativen Aufgaben von Journalismus geknüpft, Öffentlichkeit herzustellen, in der gesellschaftliche Diskurse effektiv geführt werden können. Dieser Beitrag beschreibt die analoge sowie die digitale Vertriebsorganisation mit einem Fokus auf verlagseigenen Vertrieb am Beispiel von automatisierten Recommender-Systemen sowie verlagsfremden Vertrieb in Form von neuen Intermediären wie Online-Kiosken, Social Media-Plattformen, Suchmaschinen sowie Service-Intermediären. Damit legt das Kapitel eine Grundlage zum Entwurf einer digitalen Vertriebsmatrix zum Erhalt der gesellschaftlichen Funktion tagesaktueller Verlagsmedien., Daily newspaper publishers in German-speaking countries continue to face significant challenges in mastering the digital transformation. In particular, the media houses must also manage the change from an analogue to a digital distribution organisation. The choice of distribution channels is closely linked to the normative tasks of journalism to create a public sphere in which social discourse can be effectively conducted. This article describes the analogue and the digital distribution organisation with a focus on in-house managed distribution using the example of automated recommender systems as well as external distribution by new intermediaries such as online kiosks, social media platforms, search engines, and service intermediaries. The chapter thus lays a foundation for designing a digital distribution matrix to maintain the social function of daily publishing media.

News recommender systems provide a technological architecture that helps shaping public discourse. Following a normative approach to news recommender system design, we test utility and external effects of a diversity-aware news recommender algorithm. In an experimental study using a custom-built news app, we show that diversity-optimized recommendations (1) perform similar to methods optimizing for user preferences regarding user utility, (2) that diverse news recommendations are related to a higher tolerance for opposing views, especially for politically conservative users, and (3) that diverse news recommender systems may nudge users towards preferring news with differing or even opposing views. We conclude that diverse news recommendations can have a depolarizing capacity for democratic societies.