MediaFutures Annual Meeting 2021 – Registration is now open!

Presented by Jannie Møller Hartley, Associate Professor & Vice-head of the interdisciplinary Centre for Big data CeBiDa, Department of Communication and Arts, Roskilde University Roskilde University.

Abstract:

As platforms and other algorithmic systems have become increasingly important constituents of contemporary societies, data-analytics driven practices increasingly reshape the frameworks and functions of social and economic systems. As part of this development, they also shape how journalism engages, interacts with, and cultivates its publics.

In this talk Jannie Møller Hartley explores how news production and imaginaries of the public change in the age of datafication. Drawing on interviews and ethnographic field work she surveys three four blocks of the datafication of publics namely 1) The disassembling of ‘the user’ as collective publics 2) The disassembling of the constitution of ‘the news’ 3) The algorithmic disassembling of ‘news values’ and re-assembling of algorithmic news values 4) the datafication of audiences civic engagement with the media. The talk dissects the consequences, beyond the increasingly messy relationship between news publishers and platforms and critically questions the algorithmic and data-driven shaping and cultivation of publics, and a potential reconfiguration of the very idea of a public – as Journalism moves from deciding to designing the news.

Bio:

Jannie Møller Hartley is an associate professor at Roskilde University. She is currently leading the Velux funded DataPublics project, the research group Journalism and Democracy and the interdisciplinary Big Data Centre at RUC. She has been researching the digital transformation of journalism in the cross-section between audience’s use of news and journalistic news production since news media started moving online. As a former journalist she is deeply involved in the practical development of the field, from implementing open source methods in investigate journalism to the creation of ethical and value sensitive recommender systems with data scientists inside news organisations.  

Presented by Prof. Brita Ytre-Arne, University of Bergen

Abstract:

With the datafication of everyday life, increasingly powerful platforms and intensified competition for attention, media users face a media environment which is increasingly perceived as intrusive and exploitative of their data traces. This situation causes ambivalence and resignation as well as immersive and joyful media experiences. Understanding these experiences is crucial to democracy, as media use continues to be central for public connection and citizens’ information about and engagement in society. In addition to making sense of media usage through metrics such as clicks, time spent, shares or comments, critical attention to problematic representations of datafication should be bridged with broader and deeper understandings of media as experience.

The presentation will focus on the work being done in MediaFutures to address these challenges.

Bio:

Brita Ytre-Arne is professor of Media Studies at the Department of Information Science and Media Studies at the University of Bergen, co-leader of Bergen Media Use Research Group, and Work Package Leader for WP1 Understanding Media Experiences. Her main field of research is qualitative studies of audiences and media use. She is interested in how people connect to society through cross-media user patterns, on understanding the meanings of media in everyday life, and investigating the impact of datafication, algorithms and mobile technologies on our lives. She works primarily with qualitative methods including interviews and diaries. Her current projects investigate digital disconnection dilemmas, news use during the COVID-19 pandemic, and media use and climate change. Ytre-Arne has co-authored research monographs and textbooks, edited anthologies and journal special issues, and published extensively in leading peer-reviewed journals in media and communication research. She has a substantial international network and was co-director for CEDAR – Consortium on Emerging Directions in Audience Research, a European research network that formulated an agenda for the future of audience research in the face of datafication and increasingly digital societies.

Hallvard Moe is Professor of Media Studies at the Department of Information Science and Media Studies, University of Bergen. He is also head of Bergen Media Research group with Brita Ytre-Arne, and co-leader for WP1 Understanding Media Experiences. Moe is interested in the role of media in democracy, and has researched public service broadcasting policy, and media policy more generally. He has worked on issues with media and the public sphere theoretically as well as empirically, combining a historical interest with analyses of online media from blogs to Twitter. Moe has co-authored textbooks in media studies, co-written research monographs, co-edited anthologies and journal special issues, and published around 35 articles in peer-reviewed journals as well as around 20 book chapters.

Presented by Assoc. Prof. Mehdi Elahi, University of Bergen

Abstract:

In recent years, the ever-growing production of the media content has become a challenge for the users of media applications to find the relevant content (e.g., news articles and videos) to consume. Recommendation and personalization approaches can be potential solutions to empower media applications to support their users in discovering relevant media content and to keep them engaged. The main challenge in this context is that these approaches have little potential for the discovery of new types of media content for the users and hence might cause a number of undesired effects, e.g., the popular content becoming more popular.

In WP2 of SFI MediaFutures, we will address this challenge by developing novel models that can lead to a responsible recommendation and personalization. Such models will result in enhancing the user engagement and satisfaction by utilizing novel mechanisms, e.g., expanding recommendation diversity to cover a rich spectrum of media content and ensuring that the niche or minority content is recommended to users.

Bio:

Mehdi Elahi is an Associate Professor at the University of Bergen (UiB) and the leader of WP2 at SFI MediaFutures focused on User Modeling, Personalisation & Engagement. Mehdi Elahi has obtained his Ph.D. degree in Computer Science and since then, has published more than 70 peer-reviewed journal and conference publications. His current #citation is 2100+ and his h-index is 22. His research has been mainly focused on AI, Data Science, and Cognitive Science, and their potential industrial applications such as on recommendation and personalization systems. He has co-invented and co-owned an AI-related US-patent and received prestigious research credits from big-tech IT industries (i.e., Amazon and Google). He has organized international Data Challenges together with top Companies (i.e., Spotify and XING). His research findings have been published in some of the most prestigious reference literature of the field (e.g., Recommender Systems Handbook). One of his journal articles has been the 2^nd most cited paper of a top Elsevier journal.

Christoph Trattner is a Full Professor (1404) at the University of Bergen and Center Director of the Research Centre for Responsible Media Technology & Innovation – SFI MediaFutures worth around 26 million EUR and co-leader for WP2 User Modeling, Personalisation & Engagement. He is also the founder of the DARS research group at UiB and holds a 10% Research Professor (Forsker I) position in NORCE (NKLM, department of Health) one of Norway’s largest research institutions. He is also an External Lecturer at MODUL University Vienna, Austria’s leading international private university. He received a PhD (with distinction), an MSc (with distinction) and a BSc in Computer Science and Telematics from Graz University of Technology (Austria). Trattner is an ACM Senior Member and a former Austrian Research Promotion Agency (FFG) fellow, Marshall Plan and European Research Consortium for Informatics and Mathematics (ERICM) fellow and have been working at Graz University of Technology from 2009-2012, the University of Pittsburgh from 2011-2012, the Norwegian University of Science and Technology from 2014-2015, and have been visiting Yahoo! Labs Barcelona in 2014 and CWI Amsterdam in 2015 two times. I position my research in two central specializations in the Information Science research field. Since 2009, I published over 100 scientific articles in top venues about my work and have acquired over 54 million Euros in funding on European and (inter) national level – 30 million as the PI. Examples of outlets where my work has been published includes NATURE Sustainability, JASIST, EPJ Data Science, UMUAI, WWW, AAAI ICWSM or ACM SIGIR.

Presented by Prof. Andreas Lothe Opdahl and Prof. Bjørnar Tessem, University of Bergen

Abstract:

WP3 Media Content Production & Analysis will produce novel tools for computational journalism to produce quality generated content in terms of both trustworthiness and engagement as well as fact checking software. Central research questions are: How can we computationally produce unbiased, high-quality multi-modal content effectively? How can we analyse user-generated content accurately to generate more valuable insights? 

Bio:

Andreas L. Opdahl is a Professor at the University of Bergen and work package leader of WP3 Media Content Production & Analysis. Ophdahl received his M.Eng. and Ph.D. from the Norwegian University of Science and Technology. His research interests include semantic modelling, ontologies and knowledge graphs, journalistic knowledge platforms, enterprise and IS modelling, as well as safety and security requirements. Opdahl is the author, co-author or co-editor of more than a hundred peer-reviewed research papers that have been cited several thousand times. He is a member of IFIP WG5.8 on Enterprise Interoperability and WG8.1 on Design and Evaluation of Information Systems. He serves regularly as a reviewer for premier international journals and on the program committees and as an organizer of renowned international conferences and workshops.

Bjørnar Tessem is a Professor at the University of Bergen and co-leader of WP3 Media Content Production & Analysis. Tessem holds a master in computer science (artifical intelligence, game tree search) from the University of Bergen (1985) and a PhD in computer science (artifical intelligence, Bayesian networks) from the University of Bergen (1990). He is co-leader of WP3 Media Content Production & Analysis. His research interests include artifical intelligence applied in news media analysis and content production, analogical reasoning, Bayesian networks, machine learning, and natural language understanding. Tessem has also conducted many empirical studies of software development process. He has published more than 100 scientific articles in journals, conferences, and workshops, and has led and participated in numerous projects involving artificial intelligence applied to the media and in other domains.

Presented by Senior Researcher Njål Borch, NORCE, and Prof. Morten Fjeld, University of Bergen

Abstract:

Tomorrow’s media experiences will combine sensor technology (instrumentation), AI and personal devices (interactivity) to increase engagement and collaboration. Enablers such as haptics, AR/VR, conversational AI, tangible interfaces, wearable sensors, and eyes-free interactions have made clear progress. Hence, media experiences will become more individualised, targeting the preferences and circumstances of each user (adaptation), making use of a variety of device categories offering alternative capabilities.

Research into adaptation includes responsive UIs, adaptive streaming, content adaptation and multi-device adaptation. Adaptation is also needed for collaborative and social use. Finally, media experiences must be inclusive and available for all (accessibility). Research in accessibility includes screen readers and AI-based techniques for the generation of adapted content such as audio tracks for visually impaired, video interpreters for the deaf and individualised narration.

WP4 in MediaFutures will focus on rapid prototyping and experimentation to validate approaches, ideas and user experiences. It is vital that complexity is controlled, in particular for end users, ensuring that produced knowledge is relevant for industry partners and society at large.

Bio: 

Njål Borch is a Senior Researcher at NORCE – Norwegian Research Centre and work package leader for WP4 Media Content Interaction and Accessibility. Borch’s main focus for research is on advanced multi-device systems, hyper-personalization, cloud based processing services and multi-angle streaming. Borch has been work package leader of several large, international research projects. Borch holds a PhD in computer science from the University of Tromsø, with a focus on distributed P2P search infrastructures.  Borch is also a founder and CEO of Motion Corporation, a company providing unique multi device synchronization services. The company started as a spin off from Norut (which is now part of NORCE). 

Morten Fjeld is a Professor at at the University of Bergen and co-leader of WP4 Media Content Interaction and Accessibility. Fjeld’s research activities are situated in the field of Human-Computer Interaction with a focus on tangible, tabletop, mobile, and collaborative computing. In 2005, he founded the t2i Interaction Lab at Chalmers, Sweden. He holds a dual MSc degree from NTNU (Norway) and ENSIMAG (France), and a PhD in HCI from ETH (Zurich). In 2002, Morten Fjeld received the ETH Medal for his PhD titled “Designing for Tangible Interaction”. In 2011, he was a visiting professor at NUS Singapore, in 2016 and 2017 at Tohoku University (Japan), and 2019 at ETH. Since 2019, he is a full professor at UiB. Morten Fjeld has extensive industrial experience in training systems, simulators, and user interface design.  

Presented by Prof. Lilja Øvrelid, University of Oslo, and Prof. Koenraad De Smedt, University of Bergen

Abstract:

Language technologies are at the core of media technologies. The work package 5 in MediaFutures aims to provide datasets and models for Norwegian (Bokmål/Nynorsk) that support the automated understanding as well as the automated production of media texts in this language.

WP5 adopts theoretical approaches and methodologies primarily based on linguistic data science, including neural learning. Based on language data in the media from the user partners and data and tools at the research partners, large corpora will be annotated. The labelled examples in these corpora will be used for training and evaluating supervised models that demonstrate advanced approaches in areas such as robust deep language analysis, adaptive language generation, event identification and extraction, and analysing opinions. The partners will cooperate to explore the use of such models for innovative purposes.

Bio: 

Lilja Øvrelid is a professor and group leader for the Language Technology Group (LTG) within the section for Machine Learning at the Department of Informatics, University of Oslo. Øvrelid is also work package leader for WP5 Norwegian Language Technologies. Her research focuses on various types of syntactic and semantic processing of natural language text using machine learning methods, such as dependency parsing, negation/speculation analysis and sentiment analysis. This involves both the development of resources for machine learning, the development of systems which automate syntactic and semantic analysis of language, as well as the application of these systems in downstream tasks.

Koenraad de Smedt is Professor at the University of Bergen and co-leader for WP5 Norwegian Language Technologies. de Smedt studied English and Linguistics at the University of Antwerp (Belgium) where he received his degree in 1977. He became researcher, first in Antwerp and from 1983 in Nijmegen (The Netherlands) in the areas of computational linguistics, psycholinguistics and language technology. In 1985 he became lecturer at the Dept. of Experimental Psychology in Nijmegen, where he obtained his PhD in 1990 with a dissertation titled Incremental sentence generation: A computer model of grammatical encoding. In 1993 he moved to Leiden University. Since 1995 he has been professor in Computational Linguistics at the University of Bergen (Norway) and has also been affiliated part time with Unifob and Uni Research. His research interests are in psycholinguistic models of human language processing, computational linguistics, language technology, and higher education strategies.

From 1996 to 1999 he coordinated the Norwegian partnership in a European project on automatic proofreading. From 1996 to 2000 he coordinated a large scale Socrates thematic network project on Advanced Computing in the Humanities. From 2001 to 2005 he was coordinator of the Norwegian Documentation Center for Language Technology. From 2002 he coordinated three consecutive Marie Curie training projects on language resources and technologies. From 2004 to 2008 he led the Norwegian research project TREPIL on treebanking. From 2008 he participated in CLARIN and planned and coordinated the national CLARINO research infrastructure. He is currently leading the CLARINO+ project and participates in the SFI MediaFutures.

Presented by Assoc. Prof. II Alain Starke, Wageningen University & Research / University of Bergen

Abstract:

Many web-based services and applications we use everyday provide personalized content. Among others, streaming platforms such as Netflix use recommender systems to present personalized content, based on one’s past viewing behaviour. The underlying algorithms often aim to optimize short-term engagement (e.g., to let users click on an advertisement), rather than serving one’s long-term preferences (e.g., to let users take up a healthier diet). This talk highlights how changing preferences and behaviour can be supported by recommender systems, by incorporating psychological principles into novel algorithms and using nudges in interface design. I will present lessons learned from the domains of energy conservation and healthy eating to suggest novel approaches in news personalization.

Bio:

Alain Starke performs research at the intersection of human-computer interaction, digital nudging, and behavioral change. He obtained a PhD at Eindhoven University of Technology, the Netherlands in 2019, for his work on ‘psychologically-aware’ recommender systems in the household energy-saving domain. Afterwards, he shifted his attention more towards the food and news domains. Starke is currently a postdoctoral researcher at Wageningen University & Research, the Netherlands, where he investigates how food advice can personalized to promote healthier eating habits, by personalizing both the content and the context of the advice. This theme of adapting the ‘what’ and ‘how’ of advice is also featured in his news search and recommendation work at MediaFutures, which Starke joins in the capacity of Adjunct Associate Professor at the Department of Information Science and Media Studies, University of Bergen.

Starke has been awarded multiple grants, including two personal grants: The Research Talent Grant from the Netherlands Science Organization (€200,000) and a Niels Stensen Fellowship (€60,000). He is the main author of articles in leading journals in the energy and food domain, as well as published at CORE A-level conferences, such as CHI, IUI, and RecSys.

Presented by Assoc. Prof. Nicholas Diakopoulus, Northwesterns University / University of Bergen

Abstract:

Journalists are routinely challenged with monitoring vast information environments in order to identify what is newsworthy and of interest to report to a wider audience. In a process referred to as computational news discovery, alerts and leads based on data-driven algorithmic analysis can orient journalists’ attention to events, documents, or anomalous patterns in data that are more likely to be newsworthy. In this talk I will describe the development and evaluation of several computational news discovery tools that have been designed to enable journalists in domains of social, political, and investigative journalism. Findings offer insights into journalistic practices that are enabled and transformed by such news discovery tools, and suggest opportunities for improving designs to better support those practices. Implications for journalistic sourcing, sensemaking, and sustainability will be discussed. 

Bio:

Nicholas Diakopoulos is an Associate Professor in Communication Studies and Computer Science (by courtesy) at Northwestern University where he is Director of the Computational Journalism Lab (CJL) and Director of Graduate Studies for the Technology and Social Behavior (TSB) PhD program. Diakopoulos’ research is in computational journalism with active research projects on (1) algorithmic accountability and transparency, (2) automation and algorithms in news production, and (3) social media in news contexts. He is the author of the award-winning book Automating the News: How Algorithms are Rewriting the Media from Harvard University Press. For some of his latest thinking and writing on automation and algorithms in journalism see his column in the Columbia Journalism Review.

Presented by Dr. Antske Fokkens, Full Professor, Faculty of Humanities, Language, and at Network Institute, Vrije Universiteit Amsterdam

Abstract:

Quality requirements for natural language processing tools change depending on what they are used for. In this talk, I will describe our interdisciplinary approach on diversifying news recommendation. I will illustrate what the implications are when we use the NLP task of stance detection with this goal in mind. I argue that this particular use case, introduces new demands, but at the same time, allows for a simplification avoiding one of the core challenges in the tasks current setup.

Bio: 

Antske Fokkens is a full professor in computational linguistics at the Vrije Universiteit Amsterdam, running a chair on Computational Linguistic Methods. She obtained her PhD from Saarland University working on methodology for grammar engineering. Since she moved to the Vrije Universiteit in 2012, her main line of research has been methodology for computational linguistics in digital humanities and computational social sciences. She has worked on multiple interdisciplinary projects including BiographyNet, NewsReader and a personal VENI grant project on identifying stereotyping.

Presented by Prof. Enrico Motta, Open University / University of Bergen

Abstract:

Coming soon.

Bio:

Professor Enrico Motta is a Professor of Knowledge Technologies at the Knowledge Media Institute (KMi) of the UK’s Open University and at the Department of Information Science and Media Studies of the University of Bergen. His work spans a variety of research areas to do with data science, semantic and language technologies, intelligent systems and robotics, and human-computer interaction. He has authored over 350 refereed publications and his h-index is 69. Over the years, Prof. Motta has received over £12M in external funding from a variety of institutional funding bodies, including EU, EPSRC, AHRC, the Arts Council, NERC, HEFCE, and Innovate UK.

His research has also attracted funding from commercial organizations, including the top two international scientific publishers, Elsevier and Springer Nature. Since 2014 he has been collaborating with Milton Keynes Council on its ‘smart city’ agenda, first as Director of the £17M, award-winning MK:Smart project, and then on the CityLabs and MK:5G initiatives.

Prof. Motta has also acted as advisor on strategic research programmes to several national and international organizations in a variety of countries, including UK, US, The Netherlands, Austria, Finland, and Estonia. He was Editor in Chief of the International Journal of Human Computer Studies from 2004 to 2018, one of the top international journals in HCI. In 2003 he founded the ground-breaking European Summer School on Ontological Engineering and the Semantic Web (SSSW), which provided the main international postgraduate forum for learning about semantic technologies until its final edition in 2016. The innovative pedagogic model pioneered in the SSSW series of summer schools has since been adopted by several other similar initiatives. 

His current activities include the use of AI techniques in the academic publishing industry; the deployment of intelligent robots in healthcare and urban settings; the development of sophisticated data management infrastructures for smart cities; and the use of AI techniques in computational journalism.

Presented by Prof. Oskar Juhlin, Stockholm University / University of Bergen

Abstract:

Coming soon.

Bio:

Oskar Juhlin is Professor at Stockholm University at the Departement of Computing and Systems Sciences. He is also Professor II at the Department of Information Science and Media Studies at Bergen University. He is founder and former Director of Mobile Life VinnExcellence Center. He has an interdisciplinary background spanning technology and social science. Oskar has conducted research and managed groups in many design fields such as fashion tech, social media and road traffic, animal computer interaction, and video interaction. His approach draws on combining ethnographic fieldwork of user practices with design and technical research, to generate knowledge and new applications, referred to as “associative design”. 

His research is mainly published at Conferences such as ACM CHI Conference on Human Factors in Computing Systems, Mobile HCI on Human-Computer Interaction with Mobile Devices and Services, and CSCW on Computer-Supported Cooperative Work and Social Computing.

Recently he has also been granted two patents and founded two companies (Figuracy/Shapecompanion AB and Liveling AB) in the areas of social media and fashion, as well as live video production.