@article{Opdahl2023,

title = {Trustworthy Journalism Through AI},

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

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

year  = {2023},

date = {2023-04-29},

urldate = {2023-04-29},

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

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dosMulholland2021,

title = {Deep Learning to Encourage Citizen Involvement in Local Journalism},

author = {Bjørnar Tessem and Lars Nyre and Michel dos Santos Mesquita and Paul Mulholland},

editor = {In Ville Manninen et al.},

year  = {2021},

date = {2021-12-31},

urldate = {2021-12-31},

journal = {Futures of Journalism. Palgrave Macmillan. },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cristin2000622,

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

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

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

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

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

year  = {2021},

date = {2021-12-20},

urldate = {2021-12-20},

journal = {AI and Ethics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Motta2020,

title = {Analysis and design of computational news angles},

author = {Enrico Motta and Enrico Daga and Andreas L. Opdahl and Bjørnar Tessem},

url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9127417},

doi = {10.1109/ACCESS.2020.3005513},

year  = {2020},

date = {2020-06-29},

urldate = {2020-06-29},

journal = {IEEE Access},

volume = {8},

pages = {120613-120626},

abstract = {A key skill for a journalist is the ability to assess the newsworthiness of an event or situation. To this purpose journalists often rely on news angles, conceptual criteria that are used both i) to assess whether something is newsworthy and also ii) to shape the structure of the resulting news item. As journalism becomes increasingly computer-supported, and more and more sources of potentially newsworthy data become available in real time, it makes sense to try and equip journalistic software tools with operational versions of news angles, so that, when searching this vast data space, these tools can both identify effectively the events most relevant to the target audience, and also link them to appropriate news angles. In this paper we analyse the notion of news angle and, in particular, we i) introduce a formal framework and data schema for representing news angles and related concepts and ii) carry out a preliminary analysis and characterization of a number of commonly used news angles, both in terms of our formal model and also in terms of the computational reasoning capabilities that are needed to apply them effectively to real-world scenarios. This study provides a stepping stone towards our ultimate goal of realizing a solution capable of exploiting a library of news angles to identify potentially newsworthy events in a large journalistic data space.},

note = {Pre SFI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ophdal2020,

title = {Ontologies for finding journalistic angles},

author = {Andreas L. Opdahl and Bjørnar Tessem},

url = {https://www.researchgate.net/publication/342132642_Ontologies_for_finding_journalistic_angles},

doi = {10.1007/s10270-020-00801-w},

year  = {2020},

date = {2020-06-01},

urldate = {2020-06-01},

journal = {Software and Systems Modeling},

pages = {1-17},

abstract = {Journalism relies more and more on information and communication technology (ICT). ICT-based journalistic knowledge platforms continuously harvest potentially news-relevant information from the Internet and make it useful for journalists. Because information about the same event is available from different sources and formats vary widely, knowledge graphs are emerging as a preferred technology for integrating, enriching, and preparing information for journalistic use. The paper explores how journalistic knowledge graphs can be augmented with support for news angles, which can help journalists to detect newsworthy events and make them interesting for the intended audience. We argue that finding newsworthy angles on news-related information is an important example of a topical problem in information science: that of detecting interesting events and situations in big data sets and presenting those events and situations in interesting ways},

note = {Pre SFI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Nyre2017,

title = {Business models for academic prototypes: A new approach to media innovation},

author = {Lars Nyre and Joao Ribeiro and Bjørnar Tessem},

url = {https://journals.uio.no/TJMI/article/view/2616/5101},

doi = {https://doi.org/10.5617/jomi.v4i2.2616},

year  = {2017},

date = {2017-01-18},

journal = {he Journal of Media Innovations},

volume = {4},

number = {2},

pages = {4-19},

abstract = {This article introduces the concept of academic prototypes, and shows how they can lead to technological innovation in journalism. We propose an innovation method that transforms a value-oriented academic prototype into a market-oriented journalistic service. The principles for product development presented here are based on the lean startup method as well as business model canvassing. A prototype scenario shows how the locative information app PediaCloud could be transformed into a locative news service for a regional newspaper in Western Norway. Ideally, the academic prototype will be transformed into a novel and engaging way of reading news stories, and a profitable solution for the newspaper. Realistically, the team will have acquired empirical validation of the business model's strong and weak points. In the conclusion, we summarize the utility of the approach for validated learning, and make recommendations for further research on innovation with academic prototypes.},

note = {Pre SFI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}