Keyword: algorithmic news recommenders

Algorithmic News Diversity and Democratic Theory: Adding Agonism to the Mix

Sax, M.
Digital Journalism, vol. 10, iss. : 10, pp: 1650-1670, 2022

Abstract

The role news recommenders can play in stimulating news diversity is receiving increasing amounts of attention. Democratic theory plays an important role in this debate because it helps explain why news diversity is important and which kinds of news diversity should be pursued. In this article, I observe that the current literature on news recommenders and news diversity largely draws on a narrow set of theories of liberal and deliberative democracy. Another strand of democratic theory often referred to as ‘agonism’ is often ignored. This, I argue, is a mistake. Liberal and deliberative theories of democracy focus on the question of how political disagreements and conflicts can be resolved in a rational and legitimate manner. Agonism, to the contrary, stresses the ineradicability of conflict and the need to make conflict productive. This difference in thinking about the purpose of democratic politics can also lead to new ways of thinking about the value of news diversity and role algorithmic news recommenders should play in promoting it. The overall aim of the article is (re)introduce agonistic theory to the news recommender context and to argue that agonism deserves more serious attention.

agonism, algorithmic news recommenders, Democracy, diversity, Media law, news recommenders

Bibtex

Article{nokey, title = {Algorithmic News Diversity and Democratic Theory: Adding Agonism to the Mix}, author = {Sax, M.}, doi = {https://doi.org/10.1080/21670811.2022.2114919}, year = {2022}, date = {2022-09-14}, journal = {Digital Journalism}, volume = {10}, issue = {10}, pages = {1650-1670}, abstract = {The role news recommenders can play in stimulating news diversity is receiving increasing amounts of attention. Democratic theory plays an important role in this debate because it helps explain why news diversity is important and which kinds of news diversity should be pursued. In this article, I observe that the current literature on news recommenders and news diversity largely draws on a narrow set of theories of liberal and deliberative democracy. Another strand of democratic theory often referred to as ‘agonism’ is often ignored. This, I argue, is a mistake. Liberal and deliberative theories of democracy focus on the question of how political disagreements and conflicts can be resolved in a rational and legitimate manner. Agonism, to the contrary, stresses the ineradicability of conflict and the need to make conflict productive. This difference in thinking about the purpose of democratic politics can also lead to new ways of thinking about the value of news diversity and role algorithmic news recommenders should play in promoting it. The overall aim of the article is (re)introduce agonistic theory to the news recommender context and to argue that agonism deserves more serious attention.}, keywords = {agonism, algorithmic news recommenders, Democracy, diversity, Media law, news recommenders}, }

Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content external link

Reuver, M., Mattis, N., Sax, M., Verberne, S., Tintarev, N., Helberger, N., Müller, J., Vrijenhoek, S., Fokkens, A. & Van Atteveldt, W.
The 1st Workshop on NLP for Positive Impact: NLP4PosImpact 2021 : proceedings of the workshop, pp: 47-59, 2021

algorithmic news recommenders, diversity, diversity metrics

Bibtex

Article{Reuver2021, title = {Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content}, author = {Reuver, M. and Mattis, N. and Sax, M. and Verberne, S. and Tintarev, N. and Helberger, N. and Müller, J. and Vrijenhoek, S. and Fokkens, A. and Van Atteveldt, W.}, url = {https://aclanthology.org/2021.nlp4posimpact-1.6/}, doi = {https://doi.org/https://doi.org/10.18653/v1/2021.nlp4posimpact-1.6}, year = {0801}, date = {2021-08-01}, journal = {The 1st Workshop on NLP for Positive Impact: NLP4PosImpact 2021 : proceedings of the workshop}, keywords = {algorithmic news recommenders, diversity, diversity metrics}, }

Safeguarding the Journalistic DNA: Attitudes towards the Role of Professional Values in Algorithmic News Recommender Designs external link

Bastian, M., Helberger, N. & Makhortykh, M.
Digital Journalism, 2021

Abstract

In contrast to the extensive debate on the influence of algorithmic news recommenders (ANRs) on individual news diets, the interaction between such systems and journalistic norms and missions remain under-studied. The change in the relationship between journalists and the audience caused by the transition to personalized news delivery has profound consequences for the understanding of what journalism should be. To investigate how media practitioners perceive the impact of ANRs on their professional norms and media organizations’ missions, and how these norms and missions can be integrated into ANR design, this article looks at two quality newspapers from the Netherlands and Switzerland. Using an interview-based approach conducted with practitioners in different departments (e.g. journalists, data scientists, and product managers), it explores how ANRs interact with organization-centred and audience-centred journalistic values. The paper’s findings indicate a varying degree of prominence for specific values between individual practitioners in the context of their perception of ANRs. At the same time, the paper also reveals that some organization-centred (e.g. transparency) and most audience-centred (e.g. usability) values are viewed as prerequisites for successful ANR design by practitioners with different professional backgrounds.

algorithmic news recommenders, algoritmen, frontpage, Journalistiek, Mediarecht

Bibtex

Article{Bastian2021, title = {Safeguarding the Journalistic DNA: Attitudes towards the Role of Professional Values in Algorithmic News Recommender Designs}, author = {Bastian, M. and Helberger, N. and Makhortykh, M.}, url = {https://www.tandfonline.com/doi/full/10.1080/21670811.2021.1912622}, doi = {https://doi.org/https://doi.org/10.1080/21670811.2021.1912622}, year = {0729}, date = {2021-07-29}, journal = {Digital Journalism}, abstract = {In contrast to the extensive debate on the influence of algorithmic news recommenders (ANRs) on individual news diets, the interaction between such systems and journalistic norms and missions remain under-studied. The change in the relationship between journalists and the audience caused by the transition to personalized news delivery has profound consequences for the understanding of what journalism should be. To investigate how media practitioners perceive the impact of ANRs on their professional norms and media organizations’ missions, and how these norms and missions can be integrated into ANR design, this article looks at two quality newspapers from the Netherlands and Switzerland. Using an interview-based approach conducted with practitioners in different departments (e.g. journalists, data scientists, and product managers), it explores how ANRs interact with organization-centred and audience-centred journalistic values. The paper’s findings indicate a varying degree of prominence for specific values between individual practitioners in the context of their perception of ANRs. At the same time, the paper also reveals that some organization-centred (e.g. transparency) and most audience-centred (e.g. usability) values are viewed as prerequisites for successful ANR design by practitioners with different professional backgrounds.}, keywords = {algorithmic news recommenders, algoritmen, frontpage, Journalistiek, Mediarecht}, }

On the Democratic Role of News Recommenders external link

Helberger, N.
Digital Journalism, vol. 7, num: 8, pp: 993-1012, 2019

Abstract

Are algorithmic news recommenders a threat to the democratic role of the media? Or are they an opportunity, and, if so, how would news recommenders need to be designed to advance values and goals that we consider essential in a democratic society? These are central questions in the ongoing academic and policy debate about the likely implications of data analytics and machine learning for the democratic role of the media and the shift from traditional mass-media modes of distribution towards more personalised news and platforms Building on democratic theory and the growing body of literature about the digital turn in journalism, this article offers a conceptual framework for assessing the threats and opportunities around the democratic role of news recommenders, and develops a typology of different ‘democratic recommenders’.

AI public sphere, algorithmic news recommenders, democratic role of the media, democratic theories, diversity, frontpage, Mediarecht

Bibtex

Article{Helberger2019b, title = {On the Democratic Role of News Recommenders}, author = {Helberger, N.}, url = {https://www.tandfonline.com/doi/full/10.1080/21670811.2019.1623700}, doi = {https://doi.org/10.1080/21670811.2019.1623700}, year = {0628}, date = {2019-06-28}, journal = {Digital Journalism}, volume = {7}, number = {8}, pages = {993-1012}, abstract = {Are algorithmic news recommenders a threat to the democratic role of the media? Or are they an opportunity, and, if so, how would news recommenders need to be designed to advance values and goals that we consider essential in a democratic society? These are central questions in the ongoing academic and policy debate about the likely implications of data analytics and machine learning for the democratic role of the media and the shift from traditional mass-media modes of distribution towards more personalised news and platforms Building on democratic theory and the growing body of literature about the digital turn in journalism, this article offers a conceptual framework for assessing the threats and opportunities around the democratic role of news recommenders, and develops a typology of different ‘democratic recommenders’.}, keywords = {AI public sphere, algorithmic news recommenders, democratic role of the media, democratic theories, diversity, frontpage, Mediarecht}, }

Selling News to Audiences – A Qualitative Inquiry into the Emerging Logics of Algorithmic News Personalization in European Quality News Media external link

Bodó, B.
Digital Journalism, vol. 7, num: 8, pp: 1054-1075, 2019

Abstract

How do news organizations design and implement algorithmically personalized news services? We conducted 16 in-depth interviews with professionals working in European public service broadcasting and commercial quality news media to answer this question. The news business is undergoing rapid transformations regarding how news production is financed, how news is produced and delivered to audiences and how citizens consume news. In all of these changes algorithmic recommender systems play a role. We focus on news organizations’ own personalized news services, and analyze how they define the role of personalization in contributing to the financial success of the organization, in reaching and retaining audiences, and in fulfilling their editorial mission. We interviewed editors, journalists, technologists and business intelligence and publishing professionals to gain a structural understanding of the often conflicting goals of personalization. We found that rather than focusing on increasing short-term user engagement, European quality news media try to use news personalization to increase long-term audience loyalty. In distinction to the “platform logic of personalization”, which uses personalization to produce engagement and sell audiences to advertisers, they have developed a “news logic of personalization”, which uses personalization to sell news to audiences.

algorithmic news recommenders, business models, European news media, frontpage, interviews, Mediarecht, personalization

Bibtex

Article{Bodó2019d, title = {Selling News to Audiences – A Qualitative Inquiry into the Emerging Logics of Algorithmic News Personalization in European Quality News Media}, author = {Bodó, B.}, url = {https://doi.org/10.1080/21670811.2019.1624185}, year = {0620}, date = {2019-06-20}, journal = {Digital Journalism}, volume = {7}, number = {8}, pages = {1054-1075}, abstract = {How do news organizations design and implement algorithmically personalized news services? We conducted 16 in-depth interviews with professionals working in European public service broadcasting and commercial quality news media to answer this question. The news business is undergoing rapid transformations regarding how news production is financed, how news is produced and delivered to audiences and how citizens consume news. In all of these changes algorithmic recommender systems play a role. We focus on news organizations’ own personalized news services, and analyze how they define the role of personalization in contributing to the financial success of the organization, in reaching and retaining audiences, and in fulfilling their editorial mission. We interviewed editors, journalists, technologists and business intelligence and publishing professionals to gain a structural understanding of the often conflicting goals of personalization. We found that rather than focusing on increasing short-term user engagement, European quality news media try to use news personalization to increase long-term audience loyalty. In distinction to the “platform logic of personalization”, which uses personalization to produce engagement and sell audiences to advertisers, they have developed a “news logic of personalization”, which uses personalization to sell news to audiences.}, keywords = {algorithmic news recommenders, business models, European news media, frontpage, interviews, Mediarecht, personalization}, }