@article{nokey,

title = {Modeling news recommender systems’ conditional effects on selective exposure: evidence from two online experiments},

author = {Erik Knudsen},

url = {https://mediafutures.no/jqac047/},

year  = {2023},

date = {2023-12-23},

urldate = {2023-12-23},

journal = {Journal of Communication },

abstract = {Under which conditions do news recommender systems (NRSs) amplify or reduce selective exposure? I provide the Recommender Influenced Selective Exposure framework, which aims to enable researchers to model and study the conditional effects of NRSs on selective exposure. I empirically test this framework by studying user behavior on a news site where the choice environment is designed to systematically influence selective exposure. Through two preregistered online experiments that simulate different NRSs and unobtrusively log user behavior, I contribute empirical evidence that an NRS can increase or decrease the chance that selective exposure occurs, depending on what the NRS is designed to achieve. These insights have implications for ongoing scholarly debates on the democratic impact of NRSs.},

keywords = {WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{Opdahl2023,

title = {Trustworthy Journalism Through AI},

author = {Andreas L. Opdahl and Bjørnar Tessem and Duc-Tien Dang-Nguyen and Enrico Motta and Vinay Setty and Eivind Throndsen and Are Tverberg and Christoph Trattner},

url = {https://mediafutures.no/1-s2-0-s0169023x23000423-main/},

year  = {2023},

date = {2023-04-29},

urldate = {2023-04-29},

journal = {Data & Knowledge Engineering (DKE), Elsevier},

abstract = {Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of disinformation. At the same time, quality journalism is under pressure due to loss of revenue and competition from alternative information providers. This vision paper discusses how recent advances in Artificial Intelligence (AI), and in Machine Learning (ML) in particular, can be harnessed to support efficient production of high-quality journalism. From a news consumer perspective, the key parameter here concerns the degree of trust that is engendered by quality news production. For this reason, the paper will discuss how AI techniques can be applied to all aspects of news, at all stages of its production cycle, to increase trust.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Borchgrevink-Brækhus2023,

title = {The Burden of Subscribing: How Young People Experience Digital News Subscriptions},

author = {Marianne Borchgrevink-Brækhus and Hallvard Moe },

url = {https://mediafutures.no/the-burden-of-subscribing-how-young-people-experience-digital-news-subscriptions/},

year  = {2023},

date = {2023-04-17},

urldate = {2023-04-17},

journal = {Journalism Studies },

abstract = {This paper analyzes how young non-paying news users experience digital news subscriptions in Norway. As news organizations face

declining advertising revenues, digital subscriptions are considered the sustainable financial strategy of the future, with young people a particularly challenging group to convert. We analyze the experiences of young adults who do not pay for news and identify three key dimensions to why they do not subscribe:

lack of exclusivity, subscriptions as too time-consuming, and unattractive payment models. We also detail how the informants maneuver around paywalls, and we highlight “multiperspectivism” as an overarching concern guiding the informants’ preferences. Empirically, the paper furthers our understanding of

the challenges facing business models for journalism, especially problems with long-term, provider-specific subscriptions. Methodologically, we demonstrate how a combination of recurring interviews and a media diary matching a subscription test period yields a deeper analysis of motivations for, and

experiences with, news use. Theoretically, the paper shows how approaching news through users’ experiences can provide insights not just into what users appreciate from news but also into where they consider there is a lack of value.},

keywords = {WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{Angelsen2023,

title = {Healthiness and environmental impact of dinner recipes vary widely across developed countries},

author = {Aslaug Angelsen and Alain D. Starke and Christoph Trattner},

url = {https://www.nature.com/articles/s43016-023-00746-5.epdf?sharing_token=40Ya430P4rvls-a-rD6AztRgN0jAjWel9jnR3ZoTv0MCv_q_H5Hiyr5PONI9wVjI-lufzQ9M-10R8so3hLNxXEl4h9v7mDvGnnsrg3iMb9lzo7cBlb7piPEpD26SYhEvanGp-MZrysYNovUsb5w_lSzfXiMvc6LraPBI2yf-nJQ%3D},

year  = {2023},

date = {2023-04-06},

urldate = {2023-04-06},

journal = {Nature Food },

abstract = {Contrary to food ingredients, little is known about recipes’ healthiness or environmental impact. Here we examine 600 dinner recipes from Norway, the UK and the USA retrieved from cookbooks and the Internet. Recipe healthiness was assessed by adherence to dietary guidelines and aggregate health indicators based on front-of-pack nutrient labels, while environmental impact was assessed through greenhouse gas emissions and land use. Our results reveal that recipe healthiness strongly depends on the healthiness indicator used, with more than 70% of the recipes being classified as healthy for at least one front-of-pack label, but less than 1% comply with all dietary guidelines. All healthiness indicators correlated positively with each other and negatively with environmental impact. Recipes from the USA, found to use more red meat, have a higher environmental impact than those from Norway and the UK.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Knudsen2023,

title = {How Rally-Round-the-Flag Effects Shape Trust in the News Media: Evidence from Panel Waves before and during the COVID-19 Pandemic Crisis},

author = {Erik Knudsen and Åsta Dyrnes Nordø and Magnus Hoem Iversen},

url = {https://mediafutures.no/how-rally-round-the-flag-effects-shape-trust-in-the-news-media-evidence-from-panel-waves-before-and-during-the-covid-19-pandemic-crisis/},

year  = {2023},

date = {2023-02-23},

urldate = {2023-02-23},

journal = {Political Communication},

abstract = {In this study, we extend the literature on the rally ‘round the flag phenomenon, that is, that international crises tend to cause an increase in citizens’ approval of political institutions. We advance this literature and highlight its relevance for political communication research in three ways: 1) by theorizing and empirically testing two arguments for why rally effects should extend to trust in the news media on the institutional level, 2) by providing empirical evidence on how rally effects on trust in the media develop over time during an international crisis, and 3) by theorizing and testing the conditions under which rally effects on media trust are more likely to occur by studying heterogeneous effects. Through a panel design with a pre-crisis baseline of Norwegian citizens’ trust in news media, we find evidence to suggest that the compound effect of the COVID-19 pandemic crisis caused a long-lasting increase in trust in the news media in Norway, and that the degree of increase varied by citizens’ education and whether they belonged to a “high-risk” group. We also provide evidence to suggest that rally effects on news media trust are contingent on how important the news media is as a source of information about the crisis and the “trust nexus” between media trust and political trust. These insights extend our current understanding of how times of crisis affect trust in the news media.},

keywords = {WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{KHAN2023,

title = {Visual User-Generated Content Verification in Journalism: An Overview},

author = {Sohail Ahmed Khan and Ghazaal Sheikhi and Andreas L. Opdahl and Fazle Rabbi and Sergej Stoppel and Christoph Trattner and Duc-Tien Dang-Nguyen},

url = {https://mediafutures.no/e0ret1-visual_user-generated_content_verification_in_journalism_an_overview/},

year  = {2023},

date = {2023-01-16},

urldate = {2023-01-16},

journal = {IEEE Access},

abstract = {Over the past few years, social media has become an indispensable part of the news generation and dissemination cycle on the global stage. These digital channels along with the easy-to-use editing tools have unfortunately created a medium for spreading mis-/disinformation containing visual content. Media practitioners and fact-checkers continue to struggle with scrutinising and debunking visual user-generated content (UGC) quickly and thoroughly as verification of visual content requires a high level of expertise and could be exceedingly complex amid the existing computational tools employed in newsrooms. The aim of this study is to present a forward-looking perspective on how visual UGC verification in journalism can be transformed by multimedia forensics research. We elaborate on a comprehensive overview of the five elements of the UGC verification and propose multimedia forensics as the sixth element. In addition, different types of visual content forgeries and detection approaches proposed by the computer science research community are explained. Finally, a mapping of the available verification tools media practitioners rely on is created along with their limitations and future research directions to gain the confidence of media professionals in using multimedia forensics tools in their day-to-day routine.},

keywords = {WP3: Media Content Production and Analysis},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Monitoring the infection rate: Explaining the meaning of metrics in pandemic news experiences},

author = {John Magnus Ragnhildson Dahl and Brita Ytre-Arne},

url = {https://mediafutures.no/john-magnus-and-brita/},

year  = {2023},

date = {2023-01-03},

journal = {Journalism },

abstract = {The COVID-19 pandemic has brought forward questions of what citizens need and want from journalism in a global crisis. In this article, we analyse one particular aspect of pandemic news experiences: Preoccupation with monitoring metrics for COVID-19 infection cases, hospitalisations, and deaths, widely disseminated through journalistic news outlets. We ask why close monitoring of such metrics appeared meaningful to news users, and what these experiences can tell us about the role of journalism in the pandemic information environment. Our analysis draws on qualitative research conducted in Norway in 2020, finding users particularly devoted to monitoring metrics, both in early lockdown and during the second wave of COVID-19. To contextualize our findings, we draw on scholarship on emotional responses to data in the everyday, and on the social role of journalism. We argue that monitoring of infection rates is an expression of trust in the media as a provider of factual information, also expressed by those who are cynical towards other aspects of journalism, and we conceptualise this monitoring practice as a coping strategy to deal with the pandemic as an unknown and uncontrollable threat, involving difficult emotions of uncertainty and fear.},

keywords = {WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{Opdahl2022,

title = {Semantic Knowledge Graphs for the News: A Review},

author = {Andreas L. Opdahl and Tareq Al-Moslmi and Duc-Tien Dang-Nguyen and Marc Gallofré Ocaña},

url = {https://mediafutures.no/3543508/},

year  = {2022},

date = {2022-12-15},

urldate = {2022-12-15},

journal = {ACM Computing Surveys},

volume = {55},

issue = {7},

pages = {1-38},

abstract = {ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different volumes. Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information. It is therefore well-aligned with the needs of news producers and distributors, and it is likely to become increasingly important for the news industry. This article reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news. The purpose is to present an overview of the field; to investigate what it means; and to suggest opportunities and needs for further research and development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hauptmann2022,

title = {Research directions in recommender systems for health and well-being},

author = {Hanna Hauptmann and Alan Said and Christoph Trattner },

url = {https://mediafutures.no/s11257-022-09349-4/},

year  = {2022},

date = {2022-11-14},

urldate = {2022-11-14},

journal = {User Modeling and User-Adapted Interaction Journal },

abstract = {Recommender systems have been put to use in the entertainment and e-commerce domains for decades, and in these decades, recommender systems have grown and matured into reliable and ubiquitous systems in today’s digital landscape. Relying on this maturity, the application of recommender systems for health and well-being has seen a rise in recent years, paving the way for tailored and personalized systems that support caretakers, caregivers, and other users in the health domain. In this introduction, we give a brief overview of the stakes, the requirements, and the possibilities that recommender systems for health and well-being bring.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Borchgrevink-Brækhus2022,

title = {"Det er ikke plass til alt på internett": algoritmestyrte forsider og redaksjonelle vurderinger},

author = {Marianne Borchgrevink-Brækhus},

url = {https://mediafutures.no/nmt-29-3-4-compressed/},

year  = {2022},

date = {2022-09-16},

urldate = {2022-09-16},

journal = {Norsk Medietidsskrif},

abstract = {Denne artikkelen er en analyse av overgangen til algoritmestyrte forsider i to store norske nettaviser. I 2019 innførte flere norske regionaviser i Schibsted-konsernet algoritmestyrte nettavisforsider. Mens sakene på forsidene tidligere ble manuelt styrt og rangert av frontsjefene, er forsidene nå i stor grad automatisert ut fra bruksdata. Algoritmer automatiserer deler av forsiden basert på salg, trafikk og nyhetsverdi, der formålet, ifølge utviklerne, er å frigjøre tid til viktigere journalistiske oppgaver og gi leserne flere relevante saker. Omleggingen har imidlertid skapt debatt og bekymring for at algoritmene kan bidra til å personalisere nyhetstilbudet og svekke opplevelsen av en felles dagsor- den. Gjennom kvalitative intervjuer med utviklere, frontsjefer og journalister i to av Norges største abonnementsavi- ser, Aftenposten og Bergens Tidende, undersøker artikkelen hvordan algoritmene systematiserer nyhetsinnholdet, og hva innføringen av algoritmene betyr for tilgangen på nyheter. Selv om forsidene til en viss grad personaliseres, viser funnene at algoritmenes nåværende utforming ikke har de samme selvforsterkende mekanismene som ofte forbindes med sosiale medier. Samtidig ser redaksjonene for seg at algoritmene i fremtiden kan bidra til likere informasjons- og nyhetstilgang blant ulike brukergrupper.



This article is an analysis of the transition to algorithm-driven front pages in two Norwegian online newspapers. In 2019, Norwegian media group Schibsted implemented front page algorithms in several of their online newspapers. While the news stories previously were ranked manually by editors, the front pages are now partly automated based on sales, clicks, and news value. According to web developers, the purpose is to free up time for more critical jour- nalistic tasks and provide their readers with more relevant content. Nevertheless, the implementation of the technol- ogy has caused concern. Critics fear that algorithms will personalize the news and weaken the experience of a shared public agenda. Drawing on qualitative interviews with web developers, front page editors, and journalists in the Nor- wegian newspapers Aftenposten and Bergens Tidende, the article examines how the front page algorithms systemize and rank news content. Although the front pages are moderately personalized, the findings show that the current design of the algorithms does not entail the self-reinforcing mechanisms associated with social media. Furthermore, news professionals imply that algorithmic curation can become essential to ensure equal access to news among dif- ferent user groups in the future.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Playful recognition: Television comedy and the politics of mediated recognition},

author = {John Magnus Dahl and Torgeir Uberg Nærland},

url = {https://mediafutures.no/10-1515_commun-2022-0046-compressed/},

doi = {https://doi.org/10.1515/commun-2022-0046},

year  = {2022},

date = {2022-07-14},

urldate = {2022-07-14},

journal = {Communication. The European Journal of Communication Research. },

abstract = {This article explores how media content may facilitate processes of recognition through playfulness and comedy. Mediated recognition is typically understood as a matter of respectful and positive representation of subaltern groups and in terms of struggles for visibility and dignity. Yet at the same time, the media address audiences in much less deferential ways that are nonetheless consequential to processes of recognition: by means of playfulness, subversion, and irreverence. This article introduces the concept of ‘playful recognition’ to account for the contradictory ways in which humor can incite recognition. The article empirically illustrates this concept drawing upon a case study of Svart Humor – a comedy show aired in Norway. On the one hand, this article explores an important yet neglected dimension of mediated recognition, on the other, it introduces a recognition perspective to the study of televised comedy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bogina2022,

title = {Considering Temporal Aspects in Recommender Systems: A Survey },

author = {Veronica Bogina and Tsvi Kuflik and Dietmar Jannach and Maria Bielikova and Michal Kompan and Christoph Trattner 

},

url = {https://mediafutures.no/revisedversion_considering_temporal_aspects_in_rs_a_survey-6/},

year  = {2022},

date = {2022-05-31},

urldate = {2022-05-31},

journal = {UMUAI journal},

abstract = {The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in var- ious domains related to user modeling, especially in recommender systems. Still, past and ongoing research, spread over several decades, provided multi- ple ad-hoc solutions, but no common understanding of the issue. There is no standardization and there is often little commonality in considering tempo- ral aspects in different applications. This may ultimately lead to the problem that application developers define ad-hoc solutions for their problems at hand, sometimes missing or neglecting aspects that proved to be effective in similar cases. Therefore, a comprehensive survey of the consideration of temporal as- pects in recommender systems is required. In this work, we provide an overview of various time-related aspects, categorize existing research, present a tempo- ral abstraction and point to gaps that require future research. We anticipate this survey will become a reference point for researchers and practitioners alike when considering the potential application of temporal aspects in their personalized applications.},

keywords = {New},

pubstate = {published},

tppubtype = {article}

}

@article{Elahi2022,

title = {Developing and Evaluating a University Recommender System},

author = {Mehdi Elahi and Alain D. Starke and Nabil El Ioini and Anna Alexander Lambrix and Christoph Trattner},

url = {https://www.frontiersin.org/articles/10.3389/frai.2021.796268/full},

doi = {https://doi.org/10.3389/frai.2021.796268},

year  = {2022},

date = {2022-02-02},

journal = {Frontiers in Artificial Intelligence },

abstract = {A challenge for many young adults is to find the right institution to follow higher education. Global university rankings are a commonly used, but inefficient tool, for they do not consider a person's preferences and needs. For example, some persons pursue prestige in their higher education, while others prefer proximity. This paper develops and evaluates a university recommender system, eliciting user preferences as ratings to build predictive models and to generate personalized university ranking lists. In Study 1, we performed offline evaluation on a rating dataset to determine which recommender approaches had the highest predictive value. In Study 2, we selected three algorithms to produce different university recommendation lists in our online tool, asking our users to compare and evaluate them in terms of different metrics (Accuracy, Diversity, Perceived Personalization, Satisfaction, and Novelty). We show that a SVD algorithm scores high on accuracy and perceived personalization, while a KNN algorithm scores better on novelty. We also report findings on preferred university features.},

keywords = {New, WP2: User Modeling Personalization and Engagement},

pubstate = {published},

tppubtype = {article}

}

@article{cristin2000622,

title = {Responsible media technology and AI: challenges and research directions},

author = {Christoph Trattner and Dietmar Jannach and Enrico Motta and Irene Costera Meijer and Nicholas Diakopoulos and Mehdi Elahi and Andreas L. Opdahl and Bjørnar Tessem and Njål Borch and Morten Fjeld and Lilja Øvrelid and Koenraad De Smedt and Hallvard Moe},

url = {https://app.cristin.no/results/show.jsf?id=2000622, Cristin

https://link.springer.com/content/pdf/10.1007/s43681-021-00126-4.pdf},

doi = {https://doi.org/10.1007/s43681-021-00126-4},

year  = {2021},

date = {2021-12-20},

urldate = {2021-12-20},

journal = {AI and Ethics},

keywords = {Cristin},

pubstate = {published},

tppubtype = {article}

}

@article{cristin1953352,

title = {Towards Responsible Media Recommendation},

author = {Mehdi Elahi and Dietmar Jannach and Lars Skjærven and Erik Knudsen and Helle Sjøvaag and Kristian Tolonen and Øyvind Holmstad and Igor Pipkin and Eivind Throndsen and Agnes Stenbom and Eivind Fiskerud and Adrian Oesch and Loek Vredenberg and Christoph Trattner},

url = {https://app.cristin.no/results/show.jsf?id=1953352, Cristin

https://link.springer.com/article/10.1007%2Fs43681-021-00107-7},

doi = {https://doi.org/10.1007/s43681-021-00107-7},

year  = {2021},

date = {2021-11-02},

journal = {AI and Ethics},

keywords = {Cristin},

pubstate = {published},

tppubtype = {article}

}

@article{Starke2021,

title = {Nudging Healthy Choices in Food Search Through Visual Attractiveness},

author = {Alain D. Starke and Martijn C. Willemsen and Christoph Trattner},

url = {https://www.frontiersin.org/articles/10.3389/frai.2021.621743/full},

doi = {10.3389/frai.2021.621743},

year  = {2021},

date = {2021-04-22},

number = {April 2021},

pages = {1-18},

abstract = {Recipe websites are becoming increasingly popular to support people in their home cooking. However, most of these websites prioritize popular recipes, which tend to be unhealthy. Drawing upon research on visual biases and nudges, this paper investigates whether healthy food choices can be supported in food search by depicting attractive images alongside recipes, as well as by re-ranking search results on health. After modelling the visual attractiveness of recipe images, we asked 239 users to search for specific online recipes and to select those they liked the most. Our analyses revealed that users tended to choose a healthier recipe if a visually attractive image was depicted alongside it, as well as if it was listed at the top of a list of search results. Even though less popular recipes were promoted this way, it did not come at the cost of a user’s level of satisfaction},

keywords = {WP2: User Modeling Personalization and Engagement},

pubstate = {published},

tppubtype = {article}

}

@article{cristin1953363,

title = {Investigating the impact of recommender systems on user-based and item-based popularity bias},

author = {Mehdi Elahi and Danial Khosh Kholgh and Mohammad Sina Kiarostami and Sorush Saghari and Shiva Parsa Rad and Marko Tkalcic},

url = {https://app.cristin.no/results/show.jsf?id=1953363, Cristin

https://www.sciencedirect.com/science/article/pii/S0306457321001436},

doi = {https://doi.org/10.1016/j.ipm.2021.102655},

year  = {2021},

date = {2021-01-01},

journal = {Information Processing & Management},

abstract = {Recommender Systems are decision support tools that adopt advanced algorithms in order to help users to find less-explored items that can be interesting for them. While recommender systems may offer a range of attractive benefits, they may also intensify undesired effects, such as the Popularity Bias, where a few popular users/items get more popular and many unpopular users/items get more unpopular.



In this paper, we study the impact of different recommender algorithms on the popularity bias in different application domains and recommendation scenarios. We have designed a comprehensive evaluation methodology by considering two different recommendation scenarios, i.e., the user-based scenario (e.g., recommending users to users to follow), and the item-based scenario (e.g., recommending items to users to consume). We have used two large datasets, Twitter and Movielens, and compared a wide range of classical and modern recommender algorithms by considering a diverse range of metrics, such as PR-AUC, RCE, Gini index, and Entropy Score.



The results have shown a substantial difference between different scenarios and different recommendation domains. According to our observations, while the recommendation of users to users may increase the popularity bias in the system, the recommendation of items to users may indeed decrease it. Moreover, while we have measured a different level of popularity bias in different languages (i.e., English, Spanish, Portuguese, and Japaneses), the above-noted phenomena has been consistently observed in all of these languages.},

keywords = {Cristin},

pubstate = {published},

tppubtype = {article}

}

@article{cristin1949655,

title = {Developing a Software Reference Architecture for Journalistic Knowledge Platforms},

author = {Marc Gallofré Ocaña and Andreas L. Opdahl},

url = {https://app.cristin.no/results/show.jsf?id=1949655, Cristin

http://ceur-ws.org/Vol-2978/saml-paper2.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {CEUR Workshop Proceedings},

keywords = {Cristin},

pubstate = {published},

tppubtype = {article}

}

@article{cristin1902285,

title = {How the public understands news media trust: An open-ended approach},

author = {Erik Knudsen and Stefan Dahlberg and Magnus Hoem Iversen and Mikael Poul Johannesson and Silje Nygaard},

url = {https://app.cristin.no/results/show.jsf?id=1902285, Cristin},

doi = {https://doi.org/10.1177/14648849211005892},

year  = {2021},

date = {2021-01-01},

journal = {Journalism - Theory, Practice & Criticism},

keywords = {Cristin},

pubstate = {published},

tppubtype = {article}

}