Erik Knudsen

@conference{nokey,

title = {C2PA Provenance Labels Increase Trust in News Platforms Across Western Countries},

author = {Christoph Trattner and Svenja Lys Forstner and Alain D. Starke and Erik Knudsen},

url = {https://mediafutures.no/c2pa_icwsm_2026/},

year  = {2026},

date = {2026-05-05},

urldate = {2026-05-05},

booktitle = {AAAI ICWSM 2026},

abstract = {Misinformation and disinformation threaten global public trust in news media. Generative AI exacerbates mistrust by making it difficult to distinguish authentic images from AI-generated ones. This study examines whether accompanying images with C2PA (Coalition for Content Provenance and Authenticity) provenance labels can restore trust. C2PA is an open standard that cryptographically secures and describes a media file’s origin and editing history. We conducted an online experiment with $N=6,114$ participants, reflecting audiences of six major news sources in the US, UK, and Norway. Each participant evaluated six news article previews with images, either accompanied by a provenance label (three levels of detail) or not. Presenting provenance metadata to participants significantly improved their perceptions of an image’s transparency and credibility, and also increased feelings of trust in a presented news source. These results show that verifiable provenance makes visual content more inspectable and strengthens brand trust. By adopting C2PA or similar frameworks, news organizations can counter AI-generated disinformation and improve audience trust.},

keywords = {},

pubstate = {forthcoming},

tppubtype = {conference}

}

@conference{percepvsreal24,

title = {Perception versus Reality: Evaluating User Awareness of Political Selective Exposure in News Recommender Systems},

author = {Alain D. Starke and Anders Sandvik Bremnes and Erik Knudsen and Damian Trilling and Christoph Trattner},

url = {https://mediafutures.no/umap2024___erik_alain_damian_anders_christoph/},

year  = {2024},

date = {2024-07-01},

urldate = {2024-07-01},

booktitle = {ACM UMAP 2024},

abstract = {News Recommender Systems (NRSs) have become increasingly pivotal in shaping the news landscape, particularly in how news is disseminated. This has also led to concerns about information diversity, especially regarding selective exposure in the realm of political news. Users may not recognize that news content presented to them is subject to selective exposure, through users that incorporate political beliefs. Within the U.S. two-party system, our research explores the interactions between NRSs and users’ ability to discern news articles that align with their political biases. We performed an online experiment (N = 160) to address the issue of user awareness and self-recognition of selective exposure within NRSs. Users were asked to select any number of news articles that matched their political orientation (i.e., Democrat or Republican) from a list of 50 news articles (5 Democrat, 5 Republican, 40 filler articles), which were either ranked saliently towards their political orientation or randomly. Contrary to expectations, our findings reveal no significant difference in article selection between participants exposed to a baseline random order and those who where presented with the more salient and easy to select version. We did observe that Republicans performed worse than Democrats in identifying aligning articles, based on precision and recall metrics.},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{behavrec2023,

title = {Understanding How News Recommender Systems Influence Selective Exposure},

author = {Khadiga Seddik and Erik Knudsen and Damian Trilling and Christoph Trattner },

url = {https://mediafutures.no/behavrec2023/},

year  = {2023},

date = {2023-09-18},

urldate = {2023-09-18},

booktitle = {Association for Computing Machinery (ACM) RecSys ’23},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}

@conference{inra2023-1,

title = {Topical Preference Trumps Other Features in News Recommendation: A Conjoint Analysis on a Representative Sample from Norway},

author = {Erik Knudsen and Alain D. Starke and Christoph Trattner },

url = {https://mediafutures.no/inra2023-1/},

year  = {2023},

date = {2023-09-18},

urldate = {2023-09-18},

booktitle = {Association for Computing Machinery (ACM) RecSys ’23},

keywords = {},

pubstate = {published},

tppubtype = {conference}

}