@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 = {Academic  prototype, Business canvas modeling, Innovation  method, Journalism, Lean  startup, WP3: Media Content Production and Analysis},

pubstate = {published},

tppubtype = {article}

}

@article{Guribye2016,

title = {The changing ecology of tools for live news reporting},

author = {Frode Guribye and Lars Nyre},

url = {https://www.tandfonline.com/doi/pdf/10.1080/17512786.2016.1259011?needAccess=true},

doi = {10.1080/17512786.2016.1259011},

issn = {1751-2794},

year  = {2016},

date = {2016-12-05},

journal = {Journalism Practice},

volume = {10},

number = {11},

pages = {1216-1230},

abstract = {Broadcast news channels provide fresh, continuously updated coverage of events, in sharp competition with other news channels in the same market. The live moment is a valuable feature, and broadcasters have always relied on teams that can react quickly to breaking news and report live from the scene. Technology plays an important role in the production of live news, and a number of tools are applied by skilled actors in what can be called an ecology of tools for live news reporting. This study explores new video tools for television news, and the tinkering conducted by the reporting teams to adapt to such tools. Six journalists and photographers at broadcaster TV 2 in Norway were interviewed about their everyday work practices out in the field, and we present the findings in an analysis where six aspects of contemporary live news reporting are explored: (1) from heavy to light equipment, (2) more live news at TV 2, (3) the practice of going live, (4) the mobility of live reporters, (5) tinkering to go live, and (6) quicker pace of production. In the concluding remarks we summarize our insights about live news reporting.},

note = {Pre SFI},

keywords = {broadcast news; ecology of tools; journalism; live reporting; mobile interaction; video applications; video journalism; visual technology, WP4: Media Content Interaction and Accessibility},

pubstate = {published},

tppubtype = {article}

}

@article{Milojevic2016,

title = {The Future of Journalism as a System, Profession and Culture: The Perception of Journalism Students},

author = {Ana Milojevic and Aleksandra Krstić and Aleksandra Ugrinić},

url = {https://www.researchgate.net/publication/312420186_The_Future_of_Journalism_as_a_System_Profession_and_Culture_The_Perception_of_Journalism_Students},

year  = {2016},

date = {2016-12-01},

journal = {Media Research},

volume = {22},

number = {2},

pages = {83-105},

abstract = {Currently, there is clear need for traditional journalism to redefi ne itself. The intention of this article is to portray the voices of future journalists in this quest. Therefore, Belgrade University journalism students were assigned to write down their contemplations about the journalism of tomorrow in essayistic form. In order to systematize their narratives, three theoretical understandings of jour-nalism are introduced based on a literature review: journalism as a societal system, profession and culture. The essays were analyzed using quantitative and qualitative content and critical discourse analyses. The students’ anticipated changes in journalism understood as a system, profession and culture are dis-cussed, with a special focus on language, in order to deconstruct how students evaluate the future of journalism. Furthermore, the article shows how students perceive their role in redefi ning journalism.},

note = {Pre SFI},

keywords = {Critical discourse analysis, Future of journalism, Journalism, Journalism studies, Students, WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{Harildstad2016,

title = {Samling av makt og myndighet},

author = {Torstein Harildstad},

url = {https://www.idunn.no/file/pdf/66910780/samling_av_makt_og_myndighet.pdf},

year  = {2016},

date = {2016-11-23},

journal = {Stat & Styring },

volume = {26},

number = {4},

pages = {32-35},

abstract = {Evnen til å utnytte IKT spiller en avgjørende rolle for verdiskapningen og velferden i Norge. Det er nå på tide å samle makt og myndighet i en kraftfull enhet, for å unngå den ødeleggende kompetansestriden mellom etater som nå finner sted.},

note = {Pre SFI},

keywords = {Makt, Myndighet, Stat},

pubstate = {published},

tppubtype = {article}

}

@article{Jannach2016,

title = {Recommender Systems - Beyond Matrix Completion},

author = {Dietmar Jannach and Alexander Tuzhilin and Markus Zanker },

url = {https://www.researchgate.net/publication/309600906_Recommender_systems---_beyond_matrix_completion},

doi = {10.1145/2891406},

year  = {2016},

date = {2016-10-01},

journal = {Communications of the ACM},

volume = {59},

number = {11},

pages = {94-102},

abstract = {Recommender systems have become a natural part of the user experience in today's online world. These systems are able to deliver value both for users and providers and are one prominent example where the output of academic research has a direct impact on the advancements in industry. In this article, we have briefy reviewed the history of this multidis-ciplinary field and looked at recent efforts in the research community to consider the variety of factors that may influence the long-term success of a recommender system. The list of open issues and success factors is still far from complete and new challenges arise constantly that require further research. For example, the huge amounts of user data and preference signals that become available through the Social Web and the Internet of Things not only leads to technical challenges such as scalability, but also to societal questions concerning user privacy. Based on our reflections on the developments in the field, we finally emphasize the need for a more holistic research approach that combines the insights of different disciplines. We urge that research focuses even more on practical problems that matter and are truly suited to increase the utility of recommendations from the viewpoint of the users.

},

note = {Pre SFI},

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

pubstate = {published},

tppubtype = {article}

}

@article{Elahi2016,

title = {A survey of active learning in collaborative filtering recommender systems},

author = {Mehdi Elahi and Francesco Ricci and Neil Rubens},

url = {https://reader.elsevier.com/reader/sd/pii/S1574013715300150?token=EA12A462FC07F42733F4F13375217A57D3FDC7F6047C133156CB1F4E4487DF24C5366547DF4530A25942F690233F2E30},

doi = {10.1016/j.cosrev.2016.05.002},

year  = {2016},

date = {2016-06-02},

journal = {Computer Science Review},

volume = {20},

pages = {29-50},

abstract = {In collaborative filtering recommender systems user’s preferences are expressed as ratings for items, and each additional rating extends the knowledge of the system and affects the system’s recommendation accuracy. In general, the more ratings are elicited from the users, the more effective the recommendations are. However, the usefulness of each rating may vary significantly, i.e., different ratings may bring a different amount and type of information about the user’s tastes. Hence, specific techniques, which are defined as “active learning strategies”, can be used to selectively choose the items to be presented to the user for rating. In fact, an active learning strategy identifies and adopts criteria for obtaining data that better reflects users’ preferences and enables to generate better recommendations.



So far, a variety of active learning strategies have been proposed in the literature. In this article, we survey recent strategies by grouping them with respect to two distinct dimensions: personalization, i.e., whether the system selected items are different for different users or not, and, hybridization, i.e., whether active learning is guided by a single criterion (heuristic) or by multiple criteria. In addition, we present a comprehensive overview of the evaluation methods and metrics that have been employed by the research community in order to test active learning strategies for collaborative filtering. Finally, we compare the surveyed strategies and provide guidelines for their usage in recommender systems.},

note = {Pre SFI},

keywords = {Active Learning, Cold Start, Collaborative filtering, New Start, New User, Preference Elicitation, Rating Elicitation, Recommender system, WP2: User Modeling Personalization and Engagement},

pubstate = {published},

tppubtype = {article}

}

@article{Rosén2016,

title = {The enrichment of lexical resources through incremental parsebanking},

author = {Victoria Rosén and Martha Thunes and Petter Haugereid and Gyri S. Losnegaard and Helge Dyvik and Paul Meurer and Gunn Lyse and Koenraad De Smedt},

url = {https://bora.uib.no/bora-xmlui/handle/1956/15680},

year  = {2016},

date = {2016-06-01},

urldate = {2016-06-01},

note = {Pre SFI},

keywords = {WP5: Norwegian Language Technologies},

pubstate = {published},

tppubtype = {article}

}

@article{Tobias2016,

title = {Alleviating the new user problem in collaborative filtering by exploiting personality information},

author = {Ignacio Fernandez Tobias and Matthias Braunhofer and Mehdi Elahi and Francesco Ricci and Ivan Cantador},

url = {https://www.researchgate.net/publication/285574429_Alleviating_the_New_User_Problem_in_Collaborative_Filtering_by_Exploiting_Personality_Information},

doi = {10.1007/s11257-016-9172-z},

year  = {2016},

date = {2016-06-01},

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

volume = {26},

number = {2-3},

pages = {221-255},

abstract = {The new user problem in recommender systems is still challenging, and there is not yet a unique solution that can be applied in any domain or situation. In this paper we analyze viable solutions to the new user problem in collaborative filtering (CF) that are based on the exploitation of user personality information: (a) personality-based CF, which directly improves the recommendation prediction model by incorporating user personality information, (b) personality-based active learning, which utilizes personality information for identifying additional useful preference data in the target recommendation domain to be elicited from the user, and (c) personality-based cross-domain recommendation, which exploits personality information to better use user preference data from auxiliary domains which can be used to compensate the lack of user preference data in the target domain. We benchmark the effectiveness of these methods on large datasets that span several domains, namely movies, music and books. Our results show that personality-aware methods achieve performance improvements that range from 6 to 94 % for users completely new to the system, while increasing the novelty of the recommended items by 3–40 % with respect to the non-personalized popularity baseline. We also discuss the limitations of our approach and the situations in which the proposed methods can be better applied, hence providing guidelines for researchers and practitioners in the field.},

note = {Pre SFI},

keywords = {Active Learning, Cold-start, Collaborative filtering, Cross-domain, Recommender systems, User Personality, WP2: User Modeling Personalization and Engagement},

pubstate = {published},

tppubtype = {article}

}

@article{Wozniak2016,

title = { RAMPARTS: Supporting sensemaking with spatially-aware mobile interactions},

author = {Pawel Wozniak and Nitesh Goyal and Przemyslaw Kucharski and Lars Lischke and Sven Mayer and Morten Fjeld},

url = {https://dl.acm.org/doi/10.1145/2858036.2858491

https://www.youtube.com/watch?v=t01yLj3xhVc},

year  = {2016},

date = {2016-05-01},

urldate = {2016-05-01},

note = {Pre SFI},

keywords = {WP4: Media Content Interaction and Accessibility},

pubstate = {published},

tppubtype = {article}

}

@article{Mutlu2016,

title = {VizRec: Recommending Personalized Visualizations},

author = {Belgin Mutlu and Eduardo Veas and Christoph Trattner},

url = {https://www.christophtrattner.info/pubs/ACM-TIIS.pdf},

year  = {2016},

date = {2016-01-01},

journal = {ACM Transactions on Interactive Intelligent Systems (TiiS)},

volume = {6},

number = {4},

pages = {1-40},

abstract = {Visualizations have a distinctive advantage when dealing with the information overload problem: since they

are grounded in basic visual cognition, many people understand them. However, creating the appropriate

representation requires specific expertise of the domain and underlying data. Our quest in this paper is to

study methods to suggest appropriate visualizations autonomously. To be appropriate, a visualization has

to follow studied guidelines to find and distinguish patterns visually, and encode data therein. Thus, a 

visualization tells a story of the underlying data; yet, to be appropriate, it has to clearly represent those aspects

of the data the viewer is interested in. Which aspects of a visualization are important to the viewer? Can

we capture and use those aspects to recommend visualizations? This paper investigates strategies to

 recommend visualizations considering different aspects of user preferences. A multi-dimensional scale is used to

estimate aspects of quality for charts for collaborative filtering. Alternatively, tag vectors describing charts

are used to recommend potentially interesting charts based on content. Finally, a hybrid approach combines

information on what a chart is about (tags) and how good it is (ratings). We present the design principles

behind VizRec, our visual recommender. We describe its architecture, the data acquisition approach with a

crowd sourced study, and the analysis of strategies for visualization recommendation.},

note = {Pre SFI},

keywords = {CCS Concepts, Collaborative filtering;, Content ranking, Human-centered computing, Information Systems, Personalization},

pubstate = {published},

tppubtype = {article}

}

@article{Borch2015b,

title = {Mediasync Report 2015: Evaluating timed playback of HTML5 Media},

author = {Njål Borch and Ingar Mæhlum Arntzen},

url = {https://norceresearch.brage.unit.no/norceresearch-xmlui/bitstream/handle/11250/2711974/Norut_Tromso_rapport_28-2015.pdf?sequence=2&isAllowed=y},

isbn = {978-82-7492-319-5},

year  = {2015},

date = {2015-12-08},

journal = {Norut},

abstract = {In this report we provide an extensive analysis of timing aspects of HTML5 Media, across a variety of browsers,

operating systems and media formats. Particularly we investigate how playback compares to the progression of

the local clock and how players respond to time-shifting and adjustments in playback-rate.

Additionally, we use the MediaSync JS library to enforce correctly timed playback for HTML5 media, and indicate

the effects this has on user experience. MediaSync is developed based on results from the above analysis.

MediaSync aims to provide a best effort solution that works across a variety of media formats, operating systems

and browser types, and does not make optimizations for specific permutations..

},

note = {Pre SFI},

keywords = {HTML5, MediaSync, WP4: Media Content Interaction and Accessibility},

pubstate = {published},

tppubtype = {article}

}

@article{Meijer2014,

title = {Checking, sharing, clicking and linking: Changing patterns of news use between 2004 and 2014.},

author = {Irene Costera Meijer and Tim Groot Kormelink},

url = {https://www.tandfonline.com/doi/pdf/10.1080/21670811.2014.937149?needAccess=true},

doi = {10.1080/21670811.2014.937149},

issn = { 2167-0811},

year  = {2014},

date = {2014-08-01},

journal = {Digital Journalism},

volume = {3},

number = {5},

pages = {664-679},

abstract = {This paper challenges the generally taken-for-granted automatic link between media platforms, media technology and news user practices. It explores what has changed in people’s news consumption by comparing patterns in news use between 2004–2005 and 2011–2014. While new, social and mobile media technologies did not unleash a revolution in people’s dealings with news, they have facilitated, deepened and broadened user practices we already found in 2004–2005: monitoring, checking, snacking, scanning, watching, viewing, reading, listening, searching and clicking. In addition, these forms of news usage appear to increasingly order, control, organize and anchor other practices and the experience of time and environment in which they occur. Meanwhile, new and mobile news practices like linking, sharing, liking, recommending, commenting and voting have not become as central to news consumption as often assumed.},

note = {Pre SFI},

keywords = {Audience Studies, Comparative Qualitative Research, Creative Mixed Methodology, Digitalization, News Consumption, WP1: Understanding Media Experiences},

pubstate = {published},

tppubtype = {article}

}

@article{Velldal2012,

title = {Speculation and negation: Rules, rankers, and the role of syntax},

author = {Erik Velldal and Lilja Øvrelid and Jonathon Read and Stephan Oepen},

url = {https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00126},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

note = {Pre SFI},

keywords = {WP5: Norwegian Language Technologies},

pubstate = {published},

tppubtype = {article}

}