The economics of algorithmic selection on the Internet

Latzer, Michael; Hollnbuchner, Katharina; Just, Natascha; Saurwein, Florian

doi:10.4337/9780857939852.00028

Cited by 53 publications

(47 citation statements)

References 15 publications

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“…Algorithms and associated forms of computational automation can be defined technically or socially (Zamith 2019). Technical definitions, common in computer and information sciences, affirm that an algorithm follows a series of predesigned steps or rules toward solving a problem (Latzer et al 2016); social definitions, more common in communication and media studies, emphasize the human-machine dynamics, institutional arrangements, and environmental conditions (among other things) that give shape to algorithms as social, cultural, and material artefacts (e.g., Gillespie 2016;Napoli 2014). Despite their long history, algorithms and automation have never been so front-and-centre as shaping forces in public life (as described well in accounts such as Bucher 2018 and Diakopoulos 2019).…”

Section: Algorithms Automation and Newsmentioning

confidence: 99%

Algorithms, Automation, and News

Thurman

Lewis

Kunert³

2019

Digital Journalism

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This special issue examines the growing importance of algorithms and automation in the gathering, composition, and distribution of news. It connects a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these articles share some of the noble ambitions of the pioneering publications on 'reporting algorithms', such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems, to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematize computational journalism by, for example, pointing out some of the challenges inherent in applying AI to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner.

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Section: Algorithms Automation and Newsmentioning

confidence: 99%

Algorithms, Automation, and News

Thurman

Lewis

Kunert³

2019

Digital Journalism

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“…Media organizations, especially in journalism, are suffering from a shrinking advertising base, fragmenting audiences, and rising competition from mobile, social, and digital media (Picard 2010;Anderson 2012). Latzer et al (2016) show that in the wider network economy the application of algorithms can have an economic impact in emerging, as well as existing, markets. They identify-amongst other applications-the economic potential of automated text generation, noting that algorithms can limit transaction costs for journalistic text production and lead to efficiency gains.…”

Section: Economicsmentioning

confidence: 99%

When Reporters Get Hands-on with Robo-Writing

2017

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The availability of data feeds, the demand for news on digital devices, and advances in algorithms are helping to make automated journalism more prevalent. This article extends the literature on the subject by analysing professional journalists' experiences with, and attitudes to, the technology. Uniquely, the participants were drawn from a range of news organizations-including the BBC, CNN, and Thomson Reuters-and had first-hand experience working with robo-writing software provided by one of the leading technology suppliers. The results reveal journalists' judgements on the limitations of automation, including the nature of its sources and the sensitivity of its "nose for news". Nonetheless, journalists believe that automated journalism will become more common, increasing the depth, breadth, specificity, and immediacy of information available. While some news organizations and consumers may benefit, such changes raise ethical and societal issues and, counter-intuitively perhaps, may increase the need for skills-news judgement, curiosity, and scepticism-that human journalists embody.

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“…The literature analyzing the impact of selection and filtering algorithms has initially focused on how to design better algorithms, famous examples of which are Shardanand and Maes (1995) and Linden et al (2003). Recently, more focus has been put on the economics and impact of such algorithms on consumers and the diversity of consumed products (See, e.g., Latzer et al (2016) for a survey).…”

Section: Related Literaturementioning

confidence: 99%

The Impact of Curation Algorithms on Social Network Content Quality and Structure

Berman

Katona

2016

SSRN Journal

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Curation algorithms are selection and ranking algorithms that social media platforms use to improve user experience. This paper analyzes the impact of curation algorithms on the number of friends consumers connect to and the quality of content created by producers. The model takes into account both vertical and horizontal differentiation and analyzes three different types of algorithms.The results show that without algorithmic curation, the number of friends an individual has and the quality of content on the platform are strategic complements. Introducing algorithmic curation makes consumers less selective in their follower lists when content quality is low. In equilibrium, producers of content receive lower payoffs because they enter into a contest leading to a prisoner's dilemma. The quality of content on the platform may increase if the marginal cost of producing this quality is high enough. Both of these effects may result theoretically in more diverse content consumption, but in equilibrium we find that a perfect filtering algorithm may reduce the horizontal distance of matched content resulting in a filter bubble. We identify an algorithm that focuses on filtering low quality items that results in higher quality of content as well as higher diversity under specific conditions.

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The economics of algorithmic selection on the Internet

Cited by 53 publications

References 15 publications

Algorithms, Automation, and News

Algorithms, Automation, and News

When Reporters Get Hands-on with Robo-Writing

The Impact of Curation Algorithms on Social Network Content Quality and Structure

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