2023
|
Modeling news recommender systems’ conditional effects on selective exposure: evidence from two online experiments Journal Article Erik Knudsen In: Journal of Communication , 2023. @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},
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 = {},
pubstate = {published},
tppubtype = {article}
}
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. |
Monitoring the infection rate: Explaining the meaning of metrics in pandemic news experiences Journal Article John Magnus Ragnhildson Dahl; Brita Ytre-Arne In: Journalism , 2023. @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}
}
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. |
2022
|
Semantic Knowledge Graphs for the News: A Review Journal Article Andreas L. Opdahl, Tareq Al-Moslmi, Duc-Tien Dang-Nguyen, Marc Gallofré Ocaña
,
Bjørnar Tessem
,
Csaba Veres
In: ACM Computing Surveys, vol. 55, iss. 7, pp. 1-38, 2022. @article{Opdahl2022,
title = {Semantic Knowledge Graphs for the News: A Review},
author = {Andreas L. Opdahl, Tareq Al-Moslmi, Duc-Tien Dang-Nguyen, Marc Gallofré Ocaña
,
Bjørnar Tessem
,
Csaba Veres
},
url = {https://mediafutures.no/3543508/},
year = {2022},
date = {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}
}
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. |
Measuring Harmful Representations in Scandinavian Language Models Conference Samia Touileb; Debora Nozza 2022. @conference{Touileb2022b,
title = {Measuring Harmful Representations in Scandinavian Language Models},
author = {Samia Touileb and Debora Nozza},
url = {https://mediafutures.no/2211-11678/},
year = {2022},
date = {2022-11-21},
urldate = {2022-11-21},
abstract = {Scandinavian countries are perceived as rolemodels when it comes to gender equality. With the advent of pre-trained language models and their widespread usage, we investigate to what extent gender-based harmful and toxic content exist in selected Scandinavian language models. We examine nine models, covering Danish, Swedish, and Norwegian, by manually creating template-based sentences and probing
the models for completion. We evaluate the completions using two methods for measuring harmful and toxic completions and provide a thorough analysis of the results. We show that Scandinavian pre-trained language models contain harmful and gender-based stereotypes with similar values across all languages.
This finding goes against the general expectations related to gender equality in Scandinavian countries and shows the possible problematic outcomes of using such models in real world settings.},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {conference}
}
Scandinavian countries are perceived as rolemodels when it comes to gender equality. With the advent of pre-trained language models and their widespread usage, we investigate to what extent gender-based harmful and toxic content exist in selected Scandinavian language models. We examine nine models, covering Danish, Swedish, and Norwegian, by manually creating template-based sentences and probing
the models for completion. We evaluate the completions using two methods for measuring harmful and toxic completions and provide a thorough analysis of the results. We show that Scandinavian pre-trained language models contain harmful and gender-based stereotypes with similar values across all languages.
This finding goes against the general expectations related to gender equality in Scandinavian countries and shows the possible problematic outcomes of using such models in real world settings. |
Research directions in recommender systems for health and well-being Journal Article Hanna Hauptmann; Alan Said; Christoph Trattner In: User Modeling and User-Adapted Interaction Journal , 2022. @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}
}
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. |
Annotating Norwegian language varieties on Twitter for Part-of-speech Workshop Petter Mæhlum, Andre Kåsen, Samia Touileb, Jeremy Barnes 2022. @workshop{Mæhlum2022,
title = {Annotating Norwegian language varieties on Twitter for Part-of-speech},
author = {Petter Mæhlum, Andre Kåsen, Samia Touileb, Jeremy Barnes},
url = {https://mediafutures.no/2022-vardial-1-7/},
year = {2022},
date = {2022-10-24},
abstract = {Norwegian Twitter data poses an interesting challenge for Natural Language Processing (NLP) tasks. These texts are difficult for models trained on standardized text in one of the two Norwegian written forms (Bokmål and Nynorsk), as they contain both the typical variation of social media text, as well as a large amount of dialectal variety. In this paper we present a novel Norwegian Twitter dataset annotated with POS-tags. We show that models trained on Universal Dependency (UD) data perform worse when evaluated against this dataset, and that models trained on Bokmål generally perform better than those trained on Nynorsk. We also see that performance on dialectal tweets is comparable to the written standards for some models. Finally we perform a detailed analysis of the errors that models commonly make on this data.},
keywords = {Natural-language processing (NLP), WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {workshop}
}
Norwegian Twitter data poses an interesting challenge for Natural Language Processing (NLP) tasks. These texts are difficult for models trained on standardized text in one of the two Norwegian written forms (Bokmål and Nynorsk), as they contain both the typical variation of social media text, as well as a large amount of dialectal variety. In this paper we present a novel Norwegian Twitter dataset annotated with POS-tags. We show that models trained on Universal Dependency (UD) data perform worse when evaluated against this dataset, and that models trained on Bokmål generally perform better than those trained on Nynorsk. We also see that performance on dialectal tweets is comparable to the written standards for some models. Finally we perform a detailed analysis of the errors that models commonly make on this data. |
360TourGuiding: Towards Virtual Reality Training for Tour Guiding Conference Duy-Nam Ly; Thanh-Thai La; Khanh-Duy Le; Cuong Nguyen; Morten Fjeld; Thanh Ngoc-Dat Tran; Minh-Triet Tran
360TourGuiding: Towards Virtual Reality Training for Tour Guiding, 2022. @conference{Ly2022,
title = {360TourGuiding: Towards Virtual Reality Training for Tour Guiding},
author = {Duy-Nam Ly and Thanh-Thai La and Khanh-Duy Le and Cuong Nguyen and Morten Fjeld and Thanh Ngoc-Dat Tran and Minh-Triet Tran
},
url = {https://mediafutures.no/3528575-3551436-compressed-4/},
year = {2022},
date = {2022-09-27},
urldate = {2022-09-27},
booktitle = {360TourGuiding: Towards Virtual Reality Training for Tour Guiding},
abstract = {Tour guiding plays an important role in turning sightseeing tours into memorable experiences. Tour guides, especially inexperienced ones, must practice intensively to perfect their craft. It is key that guides acquire knowledge about sights, in-situ presentation skills, and perfection ability to interact with and engage tourists. Therefore, tour-guide education requires on-site training at the place of interest including live tourist audiences. However, for modest budgets, such setups are costly and tourism students have to practice tour guiding at home or in simulated class-room setups. It has become a challenge for students to adequately prepare themselves for jobs in terms of relevant knowledge and skills. To tackle this problem, we propose 360TourGuiding, a VR system enabling its users to practice tour guiding with 360 travel videos plus the attendance of remote audiences participating through their mobile and personal device. This paper reports on the concept, on our design, current implementation, and on a pilot study with the current 360TourGuiding prototype. Based on qualitative feedback gained through the pilot study, we discuss possible system improvements, future system updates, and plans for empirical evaluation.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Tour guiding plays an important role in turning sightseeing tours into memorable experiences. Tour guides, especially inexperienced ones, must practice intensively to perfect their craft. It is key that guides acquire knowledge about sights, in-situ presentation skills, and perfection ability to interact with and engage tourists. Therefore, tour-guide education requires on-site training at the place of interest including live tourist audiences. However, for modest budgets, such setups are costly and tourism students have to practice tour guiding at home or in simulated class-room setups. It has become a challenge for students to adequately prepare themselves for jobs in terms of relevant knowledge and skills. To tackle this problem, we propose 360TourGuiding, a VR system enabling its users to practice tour guiding with 360 travel videos plus the attendance of remote audiences participating through their mobile and personal device. This paper reports on the concept, on our design, current implementation, and on a pilot study with the current 360TourGuiding prototype. Based on qualitative feedback gained through the pilot study, we discuss possible system improvements, future system updates, and plans for empirical evaluation. |
Examining Choice Overload across Single-list and Multi-list User Interfaces Inproceedings Forthcoming Alain Starke, Justyna Sedkowska, Mihir Chouhan; Bruce Ferwerda In: Forthcoming. @inproceedings{Starke2022,
title = {Examining Choice Overload across Single-list and Multi-list User Interfaces},
author = {Alain Starke, Justyna Sedkowska, Mihir Chouhan and Bruce Ferwerda},
url = {https://mediafutures.no/starke2022-choice-overload-preprint-submitted-to-intrs/},
year = {2022},
date = {2022-09-22},
urldate = {2022-09-19},
abstract = {Recommender systems are prone to triggering choice overload among users due to the typically large set sizes. Various applications have been developed that aim to overcome this through interface design, notably by so-called multi-list recommender systems. However, to what extent such user interface design actually reduces choice overload compared to single-list interfaces has yet to be examined. In a user study, we compared three common user interfaces (UIs) in the context of recipe recommendation: a single-list UI, a grid UI and a multi-list UI. Whereas earlier studies found differences in choice difficulty and choice satisfaction across grid-based and multi-list recommender interfaces, we observed no such differences, as the explanations were possibly not sufficiently helpful. Instead, we found that grid-based UIs and multi-list UIs had a higher perceived ease of use than a single-list UI, which in turn reduced choice difficulty. The benefits of such interfaces may, thus, lie in the organization of the UI, at least in the recipe domain.},
keywords = {},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
Recommender systems are prone to triggering choice overload among users due to the typically large set sizes. Various applications have been developed that aim to overcome this through interface design, notably by so-called multi-list recommender systems. However, to what extent such user interface design actually reduces choice overload compared to single-list interfaces has yet to be examined. In a user study, we compared three common user interfaces (UIs) in the context of recipe recommendation: a single-list UI, a grid UI and a multi-list UI. Whereas earlier studies found differences in choice difficulty and choice satisfaction across grid-based and multi-list recommender interfaces, we observed no such differences, as the explanations were possibly not sufficiently helpful. Instead, we found that grid-based UIs and multi-list UIs had a higher perceived ease of use than a single-list UI, which in turn reduced choice difficulty. The benefits of such interfaces may, thus, lie in the organization of the UI, at least in the recipe domain. |
"Det er ikke plass til alt på internett": algoritmestyrte forsider og redaksjonelle vurderinger Journal Article Marianne Borchgrevink-Brækhus In: Norsk Medietidsskrif, 2022. @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}
}
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. |
Hybrid Transformer Network for Deepfake Detection Conference Sohail Ahmed Khan; Duc-Tien Dang-Nguyen Hybrid Transformer Network for Deepfake Detection, 2022. @conference{Khan2022,
title = {Hybrid Transformer Network for Deepfake Detection},
author = {Sohail Ahmed Khan and Duc-Tien Dang-Nguyen},
url = {https://mediafutures.no/2208-05820-compressed-2/},
year = {2022},
date = {2022-08-11},
booktitle = {Hybrid Transformer Network for Deepfake Detection},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Playful recognition: Television comedy and the politics of mediated recognition Journal Article John Magnus Dahl; Torgeir Uberg Nærland In: Communication. The European Journal of Communication Research. , 2022. @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}
}
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. |
Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender System Conference Ayoub El Majjodi; Alain D. Starke; Christoph Trattner
Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender System, 2022. @conference{Majjodi2022,
title = {Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender System},
author = { Ayoub El Majjodi and Alain D. Starke and Christoph Trattner
},
url = {https://dl.acm.org/doi/10.1145/3503252.3531312?fbclid=IwAR0eb6MPuISpVs9Vfkd-ww_KN7EjbMbiGdDQnPxjayogfKbHFgkSgeLdaxs},
year = {2022},
date = {2022-07-03},
urldate = {2022-07-03},
booktitle = {Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender System},
abstract = {Food recommender systems show personalized recipes to users based on content liked previously. Despite their potential, often recommended (popular) recipes in previous studies have turned out to be unhealthy, negatively contributing to prevalent obesity problems worldwide. Changing how foods are presented through digital nudges might help, but these are usually examined in non-personalized contexts, such as a brick-and-mortar supermarket. This study seeks to support healthy food choices in a personalized interface by adding front-of-package nutrition labels to recipes in a food recommender system. After performing an offline evaluation, we conducted an online study (N = 600) with six different recommender interfaces, based on a 2 (non-personalized vs. personalized recipe advice) x 3 (No Label, Multiple Traffic Light, Nutri-Score) between-subjects design. We found that recipe choices made in the non-personalized scenario were healthier, while the use of nutrition labels (our digital nudge) reduced choice difficulty when the content was personalized.},
keywords = {New, WP2: User Modeling Personalization and Engagement},
pubstate = {published},
tppubtype = {conference}
}
Food recommender systems show personalized recipes to users based on content liked previously. Despite their potential, often recommended (popular) recipes in previous studies have turned out to be unhealthy, negatively contributing to prevalent obesity problems worldwide. Changing how foods are presented through digital nudges might help, but these are usually examined in non-personalized contexts, such as a brick-and-mortar supermarket. This study seeks to support healthy food choices in a personalized interface by adding front-of-package nutrition labels to recipes in a food recommender system. After performing an offline evaluation, we conducted an online study (N = 600) with six different recommender interfaces, based on a 2 (non-personalized vs. personalized recipe advice) x 3 (No Label, Multiple Traffic Light, Nutri-Score) between-subjects design. We found that recipe choices made in the non-personalized scenario were healthier, while the use of nutrition labels (our digital nudge) reduced choice difficulty when the content was personalized. |
Occupational Biases in Norwegian and Multilingual Language Models Workshop Samia Touileb; Lilja Øvrelid; Erik Velldal 2022. @workshop{Touileb2022,
title = {Occupational Biases in Norwegian and Multilingual Language Models},
author = {Samia Touileb and Lilja Øvrelid and Erik Velldal },
url = {https://mediafutures.no/2022-gebnlp-1-21/},
year = {2022},
date = {2022-07-01},
abstract = {In this paper we explore how a demographic distribution of occupations, along gender dimensions, is reflected in pre-trained language models. We give a descriptive assessment of the distribution of occupations, and investigate to what extent these are reflected in four Norwegian and two multilingual models. To this end, we introduce a set of simple bias probes, and perform five different tasks combining gendered pronouns, first names, and a set of occupations from the Norwegian statistics bureau. We show that language specific models obtain more accurate results, and are much closer to the real-world distribution of clearly gendered occupations. However, we see that none of the models have correct representations of the occupations that are demographically balanced between genders. We also discuss the importance of the training data on which the models were trained on, and argue that template-based bias probes can sometimes be fragile, and a simple alteration in a template can change a model’s behavior.},
keywords = {New, WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {workshop}
}
In this paper we explore how a demographic distribution of occupations, along gender dimensions, is reflected in pre-trained language models. We give a descriptive assessment of the distribution of occupations, and investigate to what extent these are reflected in four Norwegian and two multilingual models. To this end, we introduce a set of simple bias probes, and perform five different tasks combining gendered pronouns, first names, and a set of occupations from the Norwegian statistics bureau. We show that language specific models obtain more accurate results, and are much closer to the real-world distribution of clearly gendered occupations. However, we see that none of the models have correct representations of the occupations that are demographically balanced between genders. We also discuss the importance of the training data on which the models were trained on, and argue that template-based bias probes can sometimes be fragile, and a simple alteration in a template can change a model’s behavior. |
Considering Temporal Aspects in Recommender Systems: A Survey Journal Article Veronica Bogina; Tsvi Kuflik; Dietmar Jannach; Maria Bielikova; Michal Kompan; Christoph Trattner
In: UMUAI journal, 2022. @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}
}
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. |
Deep Learning to Encourage Citizen Involvement in Local Journalism Book Chapter Tessem, B.; Nyre, L.; Mesquita, M.d.S.; Mulholland, P. In: Mari K. Niemi Ville J. E. Manninen, Anthony Ridge-Newman (Ed.): Chapter 3, pp. 211-226, Palgrave Macmillan Cham, 2022. @inbook{Tessem2022,
title = {Deep Learning to Encourage Citizen Involvement in Local Journalism},
author = {Tessem, B. and Nyre, L. and Mesquita, M.d.S. and Mulholland, P.},
editor = {Ville J. E. Manninen, Mari K. Niemi, Anthony Ridge-Newman},
url = {https://link.springer.com/chapter/10.1007/978-3-030-95073-6_14},
doi = {https://doi.org/10.1007/978-3-030-95073-6_14},
year = {2022},
date = {2022-05-05},
urldate = {2022-05-05},
pages = {211-226},
publisher = {Palgrave Macmillan Cham},
chapter = {3},
abstract = {We discuss the potential of a mobile app for news tips to local newspapers to be augmented with artificial intelligence. It can be designed to encourage deliberative, consensus-oriented contributions from citizens. We presume that such an app will generate news stories from multi-modal data in the form of photos, videos, text elements, location information, and the identity of the contributor. Three scenarios are presented to show how image recognition, natural language processing, narrative construction, and other AI technologies can be applied. The scenarios address three interrelated challenges for local journalism. First, text and photos in tips are often of low quality for journalism purposes. Second, peer-to-peer dialogue about local news takes place in social media instead of in the newspaper. Third, readers lack news literacy and are prone to confrontational debates and trolling. We show how advances in deep learning technology makes it possible to propose solutions to these problems.},
keywords = {New},
pubstate = {published},
tppubtype = {inbook}
}
We discuss the potential of a mobile app for news tips to local newspapers to be augmented with artificial intelligence. It can be designed to encourage deliberative, consensus-oriented contributions from citizens. We presume that such an app will generate news stories from multi-modal data in the form of photos, videos, text elements, location information, and the identity of the contributor. Three scenarios are presented to show how image recognition, natural language processing, narrative construction, and other AI technologies can be applied. The scenarios address three interrelated challenges for local journalism. First, text and photos in tips are often of low quality for journalism purposes. Second, peer-to-peer dialogue about local news takes place in social media instead of in the newspaper. Third, readers lack news literacy and are prone to confrontational debates and trolling. We show how advances in deep learning technology makes it possible to propose solutions to these problems. |
A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications Conference Ziming Wang; Ziyi Hu; Yemao Man; Morten Fjeld A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications, 2022. @conference{Wang2022,
title = {A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications},
author = {Ziming Wang and Ziyi Hu and Yemao Man and Morten Fjeld},
year = {2022},
date = {2022-04-29},
urldate = {2022-04-29},
booktitle = {A Collaborative System of Flying and Ground Robots with Universal Physical Coupling Interface (PCI), and the Potential Interactive Applications},
abstract = {Flying and ground robots complement each other in terms of their advantages and disadvantages. We propose a collaborative system combining flying and ground robots, using a universal physical coupling interface (PCI) that allows for momentary connections and disconnections between multiple robots/devices. The proposed system may better utilize the complementary advantages of both flying and ground robots. We also describe various potential scenarios where such a system could be of benefit to interact with humans - namely, remote field works and rescue missions, transportation, healthcare, and education. Finally, we discuss the opportunities and challenges of such systems and consider deeper questions which should be studied in future work.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Flying and ground robots complement each other in terms of their advantages and disadvantages. We propose a collaborative system combining flying and ground robots, using a universal physical coupling interface (PCI) that allows for momentary connections and disconnections between multiple robots/devices. The proposed system may better utilize the complementary advantages of both flying and ground robots. We also describe various potential scenarios where such a system could be of benefit to interact with humans - namely, remote field works and rescue missions, transportation, healthcare, and education. Finally, we discuss the opportunities and challenges of such systems and consider deeper questions which should be studied in future work. |
RedirectedDoors: Redirection While Opening Doors in Virtual Reality Conference Morten Fjeld; Yukai Hoshikawa; Kazuyuki Fujita; Kazuki Takashima; Yoshifumi Kitamura RedirectedDoors: Redirection While Opening Doors in Virtual Reality., 2022. @conference{Fjeld2022,
title = {RedirectedDoors: Redirection While Opening Doors in Virtual Reality},
author = {Morten Fjeld and Yukai Hoshikawa and Kazuyuki Fujita and Kazuki Takashima and Yoshifumi Kitamura },
year = {2022},
date = {2022-03-12},
urldate = {2022-03-12},
booktitle = {RedirectedDoors: Redirection While Opening Doors in Virtual Reality.},
abstract = {We propose RedirectedDoors, a novel technique for redirection in VR focused on door-opening behavior. This technique manipulates the user's walking direction by rotating the entire virtual environment at a certain angular ratio of the door being opened, while the virtual door's position is kept unmanipulated to ensure door-opening realism. Results of a user study using two types of door-opening interfaces (with and without a passive haptic prop) revealed that the estimated detection thresholds generally showed a higher space efficiency of redirection. Following the results, we derived usage guidelines for our technique that provide lower noticeability and higher acceptability.},
keywords = {New, Virtual Reality, WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {conference}
}
We propose RedirectedDoors, a novel technique for redirection in VR focused on door-opening behavior. This technique manipulates the user's walking direction by rotating the entire virtual environment at a certain angular ratio of the door being opened, while the virtual door's position is kept unmanipulated to ensure door-opening realism. Results of a user study using two types of door-opening interfaces (with and without a passive haptic prop) revealed that the estimated detection thresholds generally showed a higher space efficiency of redirection. Following the results, we derived usage guidelines for our technique that provide lower noticeability and higher acceptability. |
Developing and Evaluating a University Recommender System Journal Article Mehdi Elahi; Alain D. Starke; Nabil El Ioini; Anna Alexander Lambrix; Christoph Trattner In: Frontiers in Artificial Intelligence , 2022. @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}
}
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. |
Deep Learning to Encourage Citizen Involvement in Local Journalism Inproceedings Bjørnar Tessem; Lars Nyre; Michel dos Santos Mesquita; Paul Mulholland In: Palgrave Macmillan, 2022. @inproceedings{cristin2023207,
title = {Deep Learning to Encourage Citizen Involvement in Local Journalism},
author = {Bjørnar Tessem and Lars Nyre and Michel dos Santos Mesquita and Paul Mulholland},
url = {https://app.cristin.no/results/show.jsf?id=2023207, Cristin},
doi = {https://doi.org/10.1007/978-3-030-95073-6_14},
year = {2022},
date = {2022-01-01},
booktitle = {Palgrave Macmillan},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
The Future Technologies in Journalism Presentation Bjørnar Tessem EBU Metadata Network 2022 Online Conference, 01.01.2022. @misc{cristin2028464,
title = {The Future Technologies in Journalism},
author = {Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=2028464, Cristin},
year = {2022},
date = {2022-01-01},
howpublished = {EBU Metadata Network 2022 Online Conference},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
|
Hybrid Recommendation of Movies based on Deep Content Features Inproceedings Tord Kvifte; Mehdi Elahi; Christoph Trattner In: Springer Nature, 2022. @inproceedings{cristin1957037,
title = {Hybrid Recommendation of Movies based on Deep Content Features},
author = {Tord Kvifte and Mehdi Elahi and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1957037, Cristin
https://aip-research-center.github.io/AIPA_workshop/2021/},
year = {2022},
date = {2022-01-01},
booktitle = {Springer Nature},
abstract = {When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list. This paper investigates hybrid recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. We have evaluated our proposed technique using a large dataset of movies and shown that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list. This paper investigates hybrid recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. We have evaluated our proposed technique using a large dataset of movies and shown that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features. |
Service-Oriented Computing - ICSOC 2021 Workshops - AIOps, STRAPS, AI-PA, and Satellite Events, Dubai, United Arab Emirates, November 22-25, 2021, Proceedings. Lecture Notes in Computer Science. Proceeding Hakim Hacid; Monther Aldwairi; Mohamed Reda Bouadjenek; Marinella Petrocchi; Noura Faci; Fatma Outay; Amin Beheshti; Lauritz Thamsen; Hai Dong 2022. @proceedings{cristin1957036,
title = {Service-Oriented Computing - ICSOC 2021 Workshops - AIOps, STRAPS, AI-PA, and Satellite Events, Dubai, United Arab Emirates, November 22-25, 2021, Proceedings. Lecture Notes in Computer Science.},
author = {Hakim Hacid and Monther Aldwairi and Mohamed Reda Bouadjenek and Marinella Petrocchi and Noura Faci and Fatma Outay and Amin Beheshti and Lauritz Thamsen and Hai Dong},
url = {https://app.cristin.no/results/show.jsf?id=1957036, Cristin
https://link.springer.com/conference/icsoc},
year = {2022},
date = {2022-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {proceedings}
}
|
2021
|
Responsible media technology and AI: challenges and research directions Journal Article Christoph Trattner; Dietmar Jannach; Enrico Motta; Irene Costera Meijer; Nicholas Diakopoulos; Mehdi Elahi; Andreas Lothe Opdahl; Bjørnar Tessem; Njål Trygve Borch; Morten Fjeld; Lilja Øvrelid; Koenraad De Smedt; Hallvard Moe In: AI and Ethics, 2021. @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 Lothe Opdahl and Bjørnar Tessem and Njål Trygve 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},
journal = {AI and Ethics},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
|
Towards Responsible Media Recommendation Journal Article Mehdi Elahi; Dietmar Jannach; Lars Skjærven; Erik Knudsen; Helle Sjøvaag; Kristian Tolonen; Øyvind Holmstad; Igor Pipkin; Eivind Throndsen; Agnes Stenbom; Eivind Fiskerud; Adrian Oesch; Loek Vredenberg; Christoph Trattner In: AI and Ethics, 2021. @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}
}
|
Når kunstig intelligens inntar redaksjonen Medium Bjørnar Tessem 2021. @media{cristin1942282,
title = {Når kunstig intelligens inntar redaksjonen},
author = {Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1942282, Cristin},
year = {2021},
date = {2021-10-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
|
WP3 2021 M3.1 Report The industrial expectations to, needs from and wishes for the work package Technical Report Are Tverberg; Ingrid Agasøster; Mads Grønbæck; Marius Monsen; Robert Strand; Kristian Eikeland; Eivind Throndsen; Lars Westvang; Tove B. Knudsen; Eivind Fiskerud; Rune Skår; Sergej Stoppel; Arne Berven; Glenn Skare Pedersen; Paul Macklin; Kenneth Cuomo; Loek Vredenberg; Kristian Tolonen; Andreas L Opdahl; Bjørnar Tessem; Csaba Veres; Duc Tien Dang Nguyen; Enrico Motta; Vinay Jayarama Setty University of Bergen, MediaFutures 2021. @techreport{Tverberg2021,
title = {WP3 2021 M3.1 Report The industrial expectations to, needs from and wishes for the work package},
author = {Are Tverberg and Ingrid Agasøster and Mads Grønbæck and Marius Monsen and Robert Strand and Kristian Eikeland and Eivind Throndsen and Lars Westvang and Tove B. Knudsen and Eivind Fiskerud and Rune Skår and Sergej Stoppel and Arne Berven and Glenn Skare Pedersen and Paul Macklin and Kenneth Cuomo and Loek Vredenberg and Kristian Tolonen and Andreas L Opdahl and Bjørnar Tessem and Csaba Veres and Duc Tien Dang Nguyen and Enrico Motta and Vinay Jayarama Setty},
url = {https://mediafutures.no/wp3-q2-2021-m3-1-report-by-the-industrial-partners-final-2/},
year = {2021},
date = {2021-07-25},
urldate = {2021-07-25},
institution = {University of Bergen, MediaFutures},
keywords = {New, WP3: Media Content Production and Analysis},
pubstate = {published},
tppubtype = {techreport}
}
|
VXSlate: Exploring Combination of Head Movements and Mobile Touch for Large Virtual Display Interaction Proceeding Khanh-Duy Le; Tanh Quang Tran; Karol Chlasta; Krzysztof Krejtz; Morten Fjeld; Andreas Kunz Association for Computing Machinery, New York, NY, USA, 2021, ISBN: 978-1-4503-8476-6. @proceedings{Kunz2021,
title = {VXSlate: Exploring Combination of Head Movements and Mobile Touch for Large Virtual Display Interaction},
author = {Khanh-Duy Le and Tanh Quang Tran and Karol Chlasta and Krzysztof Krejtz and Morten Fjeld and Andreas Kunz},
doi = {https://doi.org/10.1145/3461778.3462076},
isbn = {978-1-4503-8476-6},
year = {2021},
date = {2021-06-28},
journal = {DIS '21: Designing Interactive Systems Conference 2021},
pages = {283–297},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
keywords = {WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {proceedings}
}
|
Conversational Futures: Emancipating Conversational Interactions for Futures Worth Wanting Conference Minha Lee; Renee Noortman; Cristina Zaga; Alain D. Starke; Gijs Huisman; Kristina Andersen no. May 2021, 2021. @conference{Lee2021,
title = {Conversational Futures: Emancipating Conversational Interactions for Futures Worth Wanting},
author = {Minha Lee and Renee Noortman and Cristina Zaga and Alain D. Starke and Gijs Huisman and Kristina Andersen},
url = {https://minha-lee.github.io/files/mlee_Conversational_Futures_CHI2021.pdf},
year = {2021},
date = {2021-05-13},
number = {May 2021},
pages = {1-13},
abstract = {We present a vision for conversational user interfaces (CUIs) asprobes forspeculating with, rather than as objects to speculateabout. Popular CUIs, e.g., Alexa, are changing the way we converse,narrate, and imagine the world(s) to come. Yet, current conversa-tional interactions normatively may promote non-desirable ends,delivering a restricted range of request-response interactions withsexist and digital colonialist tendencies. Our critical design ap-proach envisions alternatives by considering how future voices canreside in CUIs as enabling probes. We present novel explorationsthat illustrate the potential of CUIs as critical design material, bycritiquing present norms and conversing with imaginary species.As micro-level interventions, we show that conversationswithdi-verse futuresthroughCUIs can persuade us to critically shape ourdiscourse on macro-scale concerns of the present, e.g., sustainabil-ity. We reflect on how conversational interactions with pluralistic,imagined futures can contribute to howbeing humanstands tochange.},
keywords = {Conversational user interfaces, critical design, design fiction, futuring, speculative design},
pubstate = {published},
tppubtype = {conference}
}
We present a vision for conversational user interfaces (CUIs) asprobes forspeculating with, rather than as objects to speculateabout. Popular CUIs, e.g., Alexa, are changing the way we converse,narrate, and imagine the world(s) to come. Yet, current conversa-tional interactions normatively may promote non-desirable ends,delivering a restricted range of request-response interactions withsexist and digital colonialist tendencies. Our critical design ap-proach envisions alternatives by considering how future voices canreside in CUIs as enabling probes. We present novel explorationsthat illustrate the potential of CUIs as critical design material, bycritiquing present norms and conversing with imaginary species.As micro-level interventions, we show that conversationswithdi-verse futuresthroughCUIs can persuade us to critically shape ourdiscourse on macro-scale concerns of the present, e.g., sustainabil-ity. We reflect on how conversational interactions with pluralistic,imagined futures can contribute to howbeing humanstands tochange. |
Nudging Healthy Choices in Food Search Through Visual Attractiveness Journal Article Alain D. Starke; Martijn C. Willemsen; Christoph Trattner In: no. April 2021, pp. 1-18, 2021. @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}
}
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 |
Automatiske nyhende Online Lars Nyre; Bjørnar Tessem Dag og Tid 2021, visited: 26.03.2021. @online{Tessem2021,
title = {Automatiske nyhende},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://www.dagogtid.no/feature/automatiske-nyhende-6.3.20626.2396ffd8e5},
year = {2021},
date = {2021-03-26},
urldate = {2021-03-26},
journal = {Dag og Tid},
number = {12},
organization = {Dag og Tid},
keywords = {WP3: Media Content Production and Analysis},
pubstate = {published},
tppubtype = {online}
}
|
Exploring Multi-List User Interfaces for Similar-Item Recommendations Conference Dietmar Jannach; Mathias Jesse; Michael Jugovac; Christoph Trattner 29th ACM International Conference on User Modeling, Adaptation and Personalization (UMAP '21) 2021. @conference{Jannach2021,
title = {Exploring Multi-List User Interfaces for Similar-Item Recommendations},
author = {Dietmar Jannach and Mathias Jesse and Michael Jugovac and Christoph Trattner},
url = {https://mediafutures.no/conference_umap_2021-2/},
year = {2021},
date = {2021-03-26},
organization = {29th ACM International Conference on User Modeling, Adaptation and Personalization (UMAP '21)},
abstract = {On many e-commerce and media streaming sites, the user inter-face (UI) consists of multiple lists of item suggestions. The itemsin each list are usually chosen based on pre-defined strategies and,e.g., show movies of the same genre or category. Such interfacesare common in practice, but there is almost no academic researchregarding the optimal design and arrangement of such multi-listUIs for recommenders. In this paper, we report the results of anexploratory user study that examined the effects of various designalternatives on the decision-making behavior of users in the con-text of similar-item recommendations. Our investigations showed,among other aspects, that decision-making is slower and more de-manding with multi-list interfaces, but that users also explore moreoptions before making a decision. Regarding the selection of thealgorithm to retrieve similar items, our study furthermore revealsthe importance of considering social-based similarity measures.},
keywords = {Recommender system, User Interface, User Study},
pubstate = {published},
tppubtype = {conference}
}
On many e-commerce and media streaming sites, the user inter-face (UI) consists of multiple lists of item suggestions. The itemsin each list are usually chosen based on pre-defined strategies and,e.g., show movies of the same genre or category. Such interfacesare common in practice, but there is almost no academic researchregarding the optimal design and arrangement of such multi-listUIs for recommenders. In this paper, we report the results of anexploratory user study that examined the effects of various designalternatives on the decision-making behavior of users in the con-text of similar-item recommendations. Our investigations showed,among other aspects, that decision-making is slower and more de-manding with multi-list interfaces, but that users also explore moreoptions before making a decision. Regarding the selection of thealgorithm to retrieve similar items, our study furthermore revealsthe importance of considering social-based similarity measures. |
VXSlate: Combining Head Movement and Mobile Touch for Large Virtual Display Interaction Conference Khanh-Duy Le; Tanh Quang Tran; Karol Chlasta; Krzysztof Krejtz; Morten Fjeld; Andreas Kunz 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE The Institute of Electrical and Electronics Engineers, Inc., 2021. @conference{Le2021b,
title = {VXSlate: Combining Head Movement and Mobile Touch for Large Virtual Display Interaction},
author = {Khanh-Duy Le and Tanh Quang Tran and Karol Chlasta and Krzysztof Krejtz and Morten Fjeld and Andreas Kunz},
url = {https://conferences.computer.org/vrpub/pdfs/VRW2021-2ANNoldm4A10Ml9f63uYC9/136700a528/136700a528.pdf
https://www.youtube.com/watch?v=N8ZJlKWj4mk&ab_channel=DuyL%C3%AAKh%C3%A1nh},
doi = { 10.1109/VRW52623.2021.00146},
year = {2021},
date = {2021-02-12},
pages = {528-529},
publisher = {IEEE The Institute of Electrical and Electronics Engineers, Inc.},
organization = {2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW).},
abstract = {Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays, using compact setups. However, interacting with large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulations, due to the lack of physical surfaces. We designed VXSlate, an interaction technique that uses a large virtual display, as an expansion of a tablet. VXSlate combines a user’s head movements, as tracked by the VR headset, and touch interaction on the tablet. The user’s head movements position both a virtual representation of the tablet and of the user’s hand on the large virtual display. The user’s multi-touch interactions perform finely-tuned content manipulations.},
keywords = {Human computer interaction, Human-centered computing, Interaction techniques, SFI MediaFutures, Virtual Reality, WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {conference}
}
Virtual Reality (VR) headsets can open opportunities for users to accomplish complex tasks on large virtual displays, using compact setups. However, interacting with large virtual displays using existing interaction techniques might cause fatigue, especially for precise manipulations, due to the lack of physical surfaces. We designed VXSlate, an interaction technique that uses a large virtual display, as an expansion of a tablet. VXSlate combines a user’s head movements, as tracked by the VR headset, and touch interaction on the tablet. The user’s head movements position both a virtual representation of the tablet and of the user’s hand on the large virtual display. The user’s multi-touch interactions perform finely-tuned content manipulations. |
MORS 2021: 1st Workshop on Multi Objective Recommender Systems Inproceedings Himan Abdollahpouri; Mehdi Elahi; Masoud Mansoury; Shaghayegh Sahebi; Zahra Nazari; Allison Chaney; Babak Loni In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956978,
title = {MORS 2021: 1st Workshop on Multi Objective Recommender Systems},
author = {Himan Abdollahpouri and Mehdi Elahi and Masoud Mansoury and Shaghayegh Sahebi and Zahra Nazari and Allison Chaney and Babak Loni},
url = {https://app.cristin.no/results/show.jsf?id=1956978, Cristin
https://dl.acm.org/doi/10.1145/3460231.3470936},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
abstract = {Historically, the main criterion for a successful recommender system was the relevance of the recommended items to the user. In other words, the only objective for the recommendation algorithm was to learn user’s preferences for different items and generate recommendations accordingly. However, real-world recommender systems are well beyond a simple objective and often need to take into account multiple objectives simultaneously. These objectives can be either from the users’ perspective or they could come from other stakeholders such as item providers or any party that could be impacted by the recommendations. Such multi-objective and multi-stakeholder recommenders present unique challenges and these challenges were the focus of the MORS workshop.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Historically, the main criterion for a successful recommender system was the relevance of the recommended items to the user. In other words, the only objective for the recommendation algorithm was to learn user’s preferences for different items and generate recommendations accordingly. However, real-world recommender systems are well beyond a simple objective and often need to take into account multiple objectives simultaneously. These objectives can be either from the users’ perspective or they could come from other stakeholders such as item providers or any party that could be impacted by the recommendations. Such multi-objective and multi-stakeholder recommenders present unique challenges and these challenges were the focus of the MORS workshop. |
Beyond Algorithmic Fairness in Recommender Systems Inproceedings Mehdi Elahi; Himan Abdollahpouri; Masoud Mansoury; Helma Torkamaan In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956964,
title = {Beyond Algorithmic Fairness in Recommender Systems},
author = {Mehdi Elahi and Himan Abdollahpouri and Masoud Mansoury and Helma Torkamaan},
url = {https://app.cristin.no/results/show.jsf?id=1956964, Cristin
https://dl.acm.org/doi/abs/10.1145/3450614.3461685},
doi = {https://doi.org/https://doi.org/10.1145/3450614.3461685},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface Inproceedings Arngeir Berge; Vegard Velle Sjøen; Alain Dominique Starke; Christoph Trattner In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956563,
title = {Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface},
author = {Arngeir Berge and Vegard Velle Sjøen and Alain Dominique Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956563, Cristin},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Exploring the effects of natural language justifications on food recommender systems Inproceedings Cataldo Musto; Alain Dominique Starke; Christoph Trattner; Amon Rapp; Giovanni Semeraro In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956541,
title = {Exploring the effects of natural language justifications on food recommender systems},
author = {Cataldo Musto and Alain Dominique Starke and Christoph Trattner and Amon Rapp and Giovanni Semeraro},
url = {https://app.cristin.no/results/show.jsf?id=1956541, Cristin},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
“Serving Each User”: Supporting Different Eating Goals Through a Multi-List Recommender Interface Inproceedings Alain Dominique Starke; Edis Asotic; Christoph Trattner In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956504,
title = {“Serving Each User”: Supporting Different Eating Goals Through a Multi-List Recommender Interface},
author = {Alain Dominique Starke and Edis Asotic and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956504, Cristin},
doi = {https://doi.org/10.1145/3460231.3474232},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Recommending Videos in Cold Start With Automatic Visual Tags Inproceedings Mehdi Elahi; Farshad Bakhshandegan Moghaddam; Reza Hosseini; Mohammad Hossein Rimaz; Nabil El Ioini; Marko Tkalcic; Christoph Trattner; Tammam Tillo In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956967,
title = {Recommending Videos in Cold Start With Automatic Visual Tags},
author = {Mehdi Elahi and Farshad Bakhshandegan Moghaddam and Reza Hosseini and Mohammad Hossein Rimaz and Nabil El Ioini and Marko Tkalcic and Christoph Trattner and Tammam Tillo},
url = {https://app.cristin.no/results/show.jsf?id=1956967, Cristin
https://dl.acm.org/doi/10.1145/3450614.3461687},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
abstract = {This paper addresses the so-called New Item problem in video Recommender Systems, as part of Cold Start. New item problem occurs when a new item is added to the system catalog, and the recommender system has no or little data describing that item. This could cause the system to fail to meaningfully recommend the new item to the users. We propose a novel technique that can generate cold start recommendation by utilizing automatic visual tags, i.e., tags that are automatically annotated by deeply analyzing the content of the videos and detecting faces, objects, and even celebrities within the videos. The automatic visual tags do not need any human involvement and have been shown to be very effective in representing the video content. In order to evaluate our proposed technique, we have performed a set of experiments using a large dataset of videos. The results have shown that the automatically extracted visual tags can be incorporated into the cold start recommendation process and achieve superior results compared to the recommendation based on human-annotated tags.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper addresses the so-called New Item problem in video Recommender Systems, as part of Cold Start. New item problem occurs when a new item is added to the system catalog, and the recommender system has no or little data describing that item. This could cause the system to fail to meaningfully recommend the new item to the users. We propose a novel technique that can generate cold start recommendation by utilizing automatic visual tags, i.e., tags that are automatically annotated by deeply analyzing the content of the videos and detecting faces, objects, and even celebrities within the videos. The automatic visual tags do not need any human involvement and have been shown to be very effective in representing the video content. In order to evaluate our proposed technique, we have performed a set of experiments using a large dataset of videos. The results have shown that the automatically extracted visual tags can be incorporated into the cold start recommendation process and achieve superior results compared to the recommendation based on human-annotated tags. |
The Cholesterol Factor: Balancing Accuracy and Health in Recipe Recommendation Through a Nutrient-Specific Metric Inproceedings Alain Dominique Starke; Christoph Trattner; Hedda Bakken; Martin Skivenesvåg Johannessen; Vegard Solberg In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956600,
title = {The Cholesterol Factor: Balancing Accuracy and Health in Recipe Recommendation Through a Nutrient-Specific Metric},
author = {Alain Dominique Starke and Christoph Trattner and Hedda Bakken and Martin Skivenesvåg Johannessen and Vegard Solberg},
url = {https://app.cristin.no/results/show.jsf?id=1956600, Cristin},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Promoting Healthy Food Choices Online: A Case for Multi-List Recommender Systems Inproceedings Alain Dominique Starke; Christoph Trattner In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956555,
title = {Promoting Healthy Food Choices Online: A Case for Multi-List Recommender Systems},
author = {Alain Dominique Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956555, Cristin},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Investigating the impact of recommender systems on user-based and item-based popularity bias Journal Article Mehdi Elahi; Danial Khosh Kholgh; Mohammad Sina Kiarostami; Sorush Saghari; Shiva Parsa Rad; Marko Tkalcic In: Information Processing & Management, 2021. @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}
}
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. |
Predicting Feature-based Similarity in the News Domain Using Human Judgments Inproceedings Alain Dominique Starke; Sebastian Øverhaug Larsen; Christoph Trattner In: Association for Computing Machinery (ACM), 2021. @inproceedings{cristin1956594,
title = {Predicting Feature-based Similarity in the News Domain Using Human Judgments},
author = {Alain Dominique Starke and Sebastian Øverhaug Larsen and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956594, Cristin},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Developing a Software Reference Architecture for Journalistic Knowledge Platforms Journal Article Marc Gallofré Ocaña; Andreas Lothe Opdahl In: CEUR Workshop Proceedings, 2021. @article{cristin1949655,
title = {Developing a Software Reference Architecture for Journalistic Knowledge Platforms},
author = {Marc Gallofré Ocaña and Andreas Lothe 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},
journal = {CEUR Workshop Proceedings},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
|
How the public understands news media trust: An open-ended approach Journal Article Erik Knudsen; Stefan Dahlberg; Magnus Hoem Iversen; Mikael Poul Johannesson; Silje Nygaard In: Journalism - Theory, Practice & Criticism, 2021. @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}
}
|
Contagious "Corona" Compounding by Journalists in a CLARIN Newspaper Monitor Corpus Inproceedings Koenraad De Smedt In: 2021. @inproceedings{cristin1918658,
title = {Contagious "Corona" Compounding by Journalists in a CLARIN Newspaper Monitor Corpus},
author = {Koenraad De Smedt},
url = {https://app.cristin.no/results/show.jsf?id=1918658, Cristin
https://ecp.ep.liu.se/index.php/clarin/article/view/10/209},
doi = {https://doi.org/https://doi.org/10.3384/ecp18010},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Changing Salty Food Preferences with Visual and Textual
Explanations in a Search Interface Journal Article Arngeir Berge; Vegard Velle Sjøen; Alain Starke; Christoph Trattner In: CEUR Workshop Proceedings, 2021. @article{cristin1933059,
title = {Changing Salty Food Preferences with Visual and Textual
Explanations in a Search Interface},
author = {Arngeir Berge and Vegard Velle Sjøen and Alain Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1933059, Cristin
http://ceur-ws.org/Vol-2903/IUI21WS-HEALTHI-2.pdf},
year = {2021},
date = {2021-01-01},
journal = {CEUR Workshop Proceedings},
abstract = {Salt is consumed at too high levels in the general population, causing high blood pressure and related health problems. In this paper, we present results of ongoing research that tries to reduce salt intake via technology and in particular from an interface perspective. In detail, this paper features results of a study that examines the extent to which visual and textual explanations in a search interface can change salty food preferences. An online user study with 200 participants demonstrates that this is possible in food search results by accompanying recipes with a visual taste map that includes salt-replacer herbs and spices in the calculation of salty taste.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Salt is consumed at too high levels in the general population, causing high blood pressure and related health problems. In this paper, we present results of ongoing research that tries to reduce salt intake via technology and in particular from an interface perspective. In detail, this paper features results of a study that examines the extent to which visual and textual explanations in a search interface can change salty food preferences. An online user study with 200 participants demonstrates that this is possible in food search results by accompanying recipes with a visual taste map that includes salt-replacer herbs and spices in the calculation of salty taste. |
Using Gender- and Polarity-Informed Models to Investigate Bias Inproceedings Samia Touileb; Lilja Øvrelid; Erik Velldal In: Association for Computational Linguistics, 2021. @inproceedings{cristin1924816,
title = {Using Gender- and Polarity-Informed Models to Investigate Bias},
author = {Samia Touileb and Lilja Øvrelid and Erik Velldal},
url = {https://app.cristin.no/results/show.jsf?id=1924816, Cristin
https://aclanthology.org/2021.gebnlp-1.8/},
doi = {https://doi.org/10.18653/v1/2021.gebnlp-1.8},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computational Linguistics},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Content Analysis and Production Presentation Bjørnar Tessem; Andreas Lothe Opdahl MediaFutures Annual Meeting 2021, 01.01.2021. @misc{cristin1942264,
title = {Content Analysis and Production},
author = {Bjørnar Tessem and Andreas Lothe Opdahl},
url = {https://app.cristin.no/results/show.jsf?id=1942264, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {MediaFutures Annual Meeting 2021},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
|
Kvifor Google-briller vart ein fiasko Medium Lars Nyre; Bjørnar Tessem Dag og Tid, 2021. @media{cristin1942262,
title = {Kvifor Google-briller vart ein fiasko},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1942262, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
|
What Matters in Professional Drone Pilots’ Practice? An Interview Study to Understand the Complexity of Their Work and Inform Human-Drone Interaction Research Proceeding Sarah Ljungblad; Yemao Man; Mehmet Aydın Baytaş; Mafalda Gamboa; Morten Fjeld; Mohammad Obaid ACM CHI on human factors in computing systems conference proceeding, 2021. @proceedings{cristin2003885,
title = {What Matters in Professional Drone Pilots’ Practice? An Interview Study to Understand the Complexity of Their Work and Inform Human-Drone Interaction Research},
author = {Sarah Ljungblad and Yemao Man and Mehmet Aydın Baytaş and Mafalda Gamboa and Morten Fjeld and Mohammad Obaid},
url = {https://app.cristin.no/results/show.jsf?id=2003885, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {ACM CHI on human factors in computing systems conference proceeding},
keywords = {Cristin},
pubstate = {published},
tppubtype = {proceedings}
}
|