Erik Knudsen; Stefan Dahlberg; Magnus H Iversen; Mikael P Johannesson; Silje Nygaard How the public understands news media trust: An open-ended approach Journal Article Journalism, (April 2021), pp. 1-17, 2021. Abstract | BibTeX | Links: @article{Knudsen2021,
title = {How the public understands news media trust: An open-ended approach},
author = {Erik Knudsen and Stefan Dahlberg and Magnus H Iversen and Mikael P Johannesson and Silje Nygaard},
url = {https://journals.sagepub.com/doi/pdf/10.1177/14648849211005892},
doi = {10.1177/14648849211005892},
year = {2021},
date = {2021-03-31},
journal = {Journalism},
number = {April 2021},
pages = {1-17},
abstract = {Despite the central role that ordinary citizens play as ‘trustors’ (i.e. the actor that places trust) in the literature on news media trust, prior quantitative studies have paid little attention to how ordinary citizens understand and define news media trust. Here, trust tends to be studied from a researcher-defined – rather than an audience-defined – perspective. To address this gap, we investigate how the public describes news media trust in their own words by asking them directly. We analyse 1500 written responses collected through a Norwegian online probability-based survey, here using a semisupervised quantitative text analysis technique called structural topic modelling (STM). We find that citizens’ own understanding of news media trust can be categorised into four distinct topics that, in some instances, are comparable to academic and professional discourse. We show that citizens’ written descriptions of news media trust vary by many of the same variables that prior research has found to be important predictors of levels of trust. Respondents’ written descriptions of news media trust vary by education and satisfaction with democracy but not other known predictors of trust, such as ideological self-placement and political preferences.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Despite the central role that ordinary citizens play as ‘trustors’ (i.e. the actor that places trust) in the literature on news media trust, prior quantitative studies have paid little attention to how ordinary citizens understand and define news media trust. Here, trust tends to be studied from a researcher-defined – rather than an audience-defined – perspective. To address this gap, we investigate how the public describes news media trust in their own words by asking them directly. We analyse 1500 written responses collected through a Norwegian online probability-based survey, here using a semisupervised quantitative text analysis technique called structural topic modelling (STM). We find that citizens’ own understanding of news media trust can be categorised into four distinct topics that, in some instances, are comparable to academic and professional discourse. We show that citizens’ written descriptions of news media trust vary by many of the same variables that prior research has found to be important predictors of levels of trust. Respondents’ written descriptions of news media trust vary by education and satisfaction with democracy but not other known predictors of trust, such as ideological self-placement and political preferences. |
Dietmar Jannach; Mathias Jesse; Michael Jugovac; Christoph Trattner Exploring Multi-List User Interfaces for Similar-Item Recommendations Conference 29th ACM International Conference on User Modeling, Adaptation and Personalization (UMAP '21) 2021. Abstract | BibTeX | Links: @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 = {},
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. |
