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- ItemA Democratic Approach to Digital Rights: Comparing Perspectives on Digital Sovereignty on the City Level(2023) Pierri, Paola; Calderón Lüning, ElizabethThis article will be drawing on two cases to reflect on the impact of different ways of practicing civic engagement in urban digitalization policy. Both cases reflect on the importance of cities playing an active role in the promotion of digital rights, obligation of public participation in digital policy making, and need for political digital education to enable democratic conversations on digital transformation. From a democratic theory point of view, the shifts happening through the digitalization of societies raise interesting questions regarding what modes of governance should be implemented for improving digital sovereignty, which could be in line with “locally” grounded politics. Theoretically, the article will frame these issues of governance and civic participation within the literature on “digital sovereignty,” understood as going beyond national territory toward issues of independence, democratic control, and autonomy over digital infrastructures, technologies, and content.
- ItemA Pandemic of Prediction. On the Circulation of Contagion Models between Public Health and Public Safety(2021) Heimstädt, Maximilian; Egbert, Simon; Esposito, ElenaDigital prediction tools increasingly complement or replace other practices of coping with an uncertain future. The current COVID-19 pandemic, it seems, is further accelerating the spread of prediction. The prediction of the pandemic yields a pandemic of prediction. In this paper, we explore this dynamic, focusing on contagion models and their transmission back and forth between two domains of society: public health and public safety. We connect this movement with a fundamental duality in the prevention of contagion risk concerning the two sides of being-at-risk and being-a-risk. Both in the spread of a disease and in the spread of criminal behavior, a person at risk can be a risk to others and vice versa. Based on key examples, from this perspective we observe and interpret a circular movement in three phases. In the past, contagion models have moved from public health to public safety, as in the case of the Strategic Subject List used in the policing activity of the Chicago Police Department. In the present COVID-19 pandemic, the analytic tools of policing wander to the domain of public health – exemplary of this movement is the cooperation between the data infrastructure firm Palantir and the UK government’s public health system NHS. The expectation that in the future the predictive capacities of digital contact tracing apps might spill over from public health to policing is currently shaping the development and use of tools such as the Corona-Warn-App in Germany. In all these cases, the challenge of pandemic governance lies in managing the connections and the exchanges between the two areas of public health and public safety while at the same time keeping the autonomy of each.
- ItemA review of technologies for collaborative online information seeking. On the contribution of collaborative argumentation(2021) Mayweg-Paus, Elisabeth; Zimmermann, Maria; Le, Nguyen-Thinh; Pinkwart, NielsIn everyday life, people seek, evaluate, and use online sources to underpin opinions and make decisions. While education must promote the skills people need to critically question the sourcing of online information, it is important, more generally, to understand how to successfully promote the acquisition of any skills related to seeking online information. This review outlines technologies that aim to support users when they collaboratively seek online information. Upon integrating psychological–pedagogical approaches on trust in and the sourcing of online information, argumentation, and computer-supported collaborative learning, we reviewed the literature (N= 95 journal articles) on technologies for collaborative online information seeking. The technologies we identified either addressed collaborative online information seeking as an exclusive process for searching for online information or, alternatively, addressed online information seeking within the context of a more complex learning process. Our review was driven by three main research questions: We aimed to understand whether and how the studies considered 1) the role of trust and critical questioning in the sourcing of online information, 2) the learning processes at play when information seekers engage in collaborative argumentation, and 3) what affordances are offered by technologies that support users’ collaborative seeking of online information. The reviewed articles that focused exclusively on technologies for seeking online information primarily addressed aspects of cooperation (e.g., task management), whereas articles that focused on technologies for integrating the processes of information seeking into the entire learning processes instead highlighted aspects of collaborative argumentation (e.g., exchange of multiple perspectives and critical questioning in argumentation). Seven of the articles referred to trust as an aspect of seekers’ sourcing strategies. We emphasize how researchers’, users’, and technology developers’ consideration of collaborative argumentation could expand the benefits of technological support for seeking online information.
- ItemActive Social Media Use and Its Impact on Well-being: An Experimental Study on the Effects of Posting Pictures on Instagram(2023) Krause, Hannes-Vincent; große Deters, Fenne; Baumann, Annika; Krasnova, Hanna
- ItemAlgorithmic Governance(2019) Katzenbach, Christian; Ulbricht, Lena
- ItemAlgorithmic Management: Bright and Dark Sides, Practical Implications, and Research Opportunities(2022) Benlian, Alexander; Wiener, Martin; Cram, Alec; Krasnova, Hanna; Mädche, Alexander; Möhlmann, Mareike; Recker, Jan; Remus, Ulrich
- ItemAlgorithmic regulation. A maturing concept for investigating regulation of and through algorithms(2022) Ulbricht, Lena; Yeung, KarenThis paper offers a critical synthesis of the articles in this Special Issue with a view to assessing the concept of “algorithmic regulation” as a mode of social coordination and control articulated by Yeung in 2017. We highlight significant changes in public debate about the role of algorithms in society occurring in the last five years. We also highlight prominent themes that emerge from the contributions, illuminating what is distinctive about the concept of algorithmic regulation, reflecting upon some of its strengths, limitations, and its relationship with the broader research field. In closing, we argue that the core concept is valuable and maturing. It has evolved into an analytical bridge that fosters cross-disciplinary development and analysis in ways that enrich its early “skeletal” form, thereby enabling careful and context-sensitive analysis of algorithmic regulation in concrete settings while facilitating critical reflection concerning the legitimacy of existing and proposed regulatory regimes.
- ItemAnonymität im Internet: Interdisziplinäre Rückschlüsse auf Freiheit und Verantwortung bei der Ausgestaltung von Kommunikationsräumen(Academia, 2021) Gräfe, Hans-Christian; Hamm, Andrea; Berger, Franz X.; Deremetz, Anne; Hennig, Martin; Michell, Alix„Die anonyme Nutzung ist dem Internet immanent.“ So lautet eine unter Juristinnen bekannte und weit verbreitete Behauptung, die sich hinterfragen lassen muss. Die Wirklichkeit im Internet zeigt ein hinreichend anderes Bild. Unternehmen, die hinter den Kulissen immense Umsätze mit personalisierter Werbung erwirtschaften, registrieren nicht nur die Webseiten, die wir besuchen, sondern erfassen als Metadaten auch jede unserer Mausbewegungen, jeden Tastendruck und jede Änderung der Scrollposition. Anhand ihrer individuellen Verhaltensmuster können Internetnutzende nicht nur identifiziert, sondern auch Aussagen über ihre Gewohnheiten und politischen Überzeugungen, ihre gesundheitliche und finanzielle Situation, ihre Persönlichkeit und vieles mehr getroffen werden.
- ItemAnti‐elitism in the European Radical Right in Comparative Perspective(2023) Vaughan, Michael; Heft, AnnettTo better understand the communication of anti-elitism in contemporary politics, this study conceptually differentiates between specific anti-elitism geared toward specific, materially powerful elites (‘Angela Merkel’) and general anti-elitism referencing broader discursive constructs (‘the elite’). The study analyses the online communications of radical right parties in the 2019 European Parliament elections from six countries (Germany, France, Italy, Austria, Poland and Sweden). This more fine-grained analysis of anti-elitism highlights some areas of transnational convergence, such as a tendency to focus on specific political elites, rather than other sectors such as the media or discursive constructs. The findings also reveal stratification according to parties’ position in national power structures: opposition parties tend to target national-level elites while governing parties focus on the European level. The findings highlight that anti-elitism is used in a highly instrumental way, and help us to better understand the intersection between anti-elitism and the multilevel politics of EP elections.
- ItemAnything Goes? Youth, News, and Democratic Engagement in the Roaring 2020s(2022) Ohme, Jakob; Andersen, Kim; Albæk, Erik; De Vreese, Claes H.In the modern world, every person will come of age in a future that is hard to foresee. However, the way citizens born today will navigate their future world will be affected by the context and the institutions that structure the world of their young life. Maybe more importantly than ever, the technologies and the information environment they grow up with shape the ways in which today’s youngsters are socialised into the political world. Youth is a reference point that can reveal two important things: the past years of a cohort's development and an outlook into the future. Every generation is specifically shaped by their formative years which in turn will influence the society in which they come of age, once they enter the job market and end up in positions of responsibility and decision-making power.
- ItemAre Campaigns Getting Uglier, and Who Is to Blame? Negativity, Dramatization and Populism on Facebook in the 2014 and 2019 EP Election Campaigns(2023) Klinger, Ulrike; Koc-Michalska, Karolina; Rußmann, Uta
- ItemAudit - and then what? A roadmap for digitization of learning factories(2019) Ullrich, André; Enke, Judith; Teichmann, Malte; Kreß, Antonio; Gronau, NorbertCurrent trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don‘t suffice the learner’s needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented.
- ItemAvoiding the news to participate in society? The longitudinal relationship between news avoidance and civic engagement(2022) Ohme, Jakob; de Bruin, Kiki; de Haan, Yael; Kruikemeier, Sanne; Van Der Meer, Toni G. L. A.; Vliegenthart, Rens
- ItemBeyond “Industry 4.0”. B2B factory networks as an alternative path towards the digital transformation of manufacturing and work(2021) Butollo, Florian; Schneidemesser, LeaThis article uses theoretical and empirical evidence of variations in digitalized manufacturing to revisit Piore and Sabel’s 1984 work on flexible specialization and to criticize the inherent one-sidedness of the Industry 4.0 discourse. This is juxtaposed with empirical findings on platform-mediated business-to-business factory networks, in which flexibility is facilitated by the digital interconnection of a far-flung network of small-scale manufacturers rather than by sophisticated production technology. The effects on work are equivocal; they entail the potential for a craft-like and skill-intensive paradigm of small-scale manufacturing that can upgrade work, but also for a race to the bottom in price-sensitive industries.
- ItemBias in data‐driven artificial intelligence systems—An introductory survey(2020) Ntoutsi, Eirini; Fafalios, Pavlos; Gadiraju, Ujwal; Iosifidis, Vasileios; Nejdl, Wolfgang; Vidal, Maria‐Esther; Ruggieri, Salvatore; Turini, Franco; Papadopoulos, Symeon; Krasanakis, Emmanouil; Kompatsiaris, Ioannis; Kinder‐Kurlanda, Katharina; Wagner, Claudia; Karimi, Fariba; Fernandez, Miriam; Alani, Harith; Berendt, Bettina; Kruegel, Tina; Heinze, Christian; Broelemann, Klaus; Kasneci, Gjergji; Tiropanis, Thanassis; Staab, SteffenArtificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well‐grounded in a legal frame. In this survey, we focus on data‐driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth.
- ItemBig Data und Governance im digitalen Zeitalter(transcript, 2019) Ulbricht, Lena; Hofmann, Jeanette; Kersting, Norbert; Ritzi, Claudia; Schünemann, Wolf
- ItemBot, or not? Comparing three methods for detecting social bots in five political discourses(2021) Martini, Franziska; Samula, Paul; Keller, Tobias R; Klinger, UlrikeSocial bots – partially or fully automated accounts on social media platforms – have not only been widely discussed, but have also entered political, media and research agendas. However, bot detection is not an exact science. Quantitative estimates of bot prevalence vary considerably and comparative research is rare. We show that findings on the prevalence and activity of bots on Twitter depend strongly on the methods used to identify automated accounts. We search for bots in political discourses on Twitter, using three different bot detection methods: Botometer, Tweetbotornot and “heavy automation”. We drew a sample of 122,884 unique user Twitter accounts that had produced 263,821 tweets contributing to five political discourses in five Western democracies. While all three bot detection methods classified accounts as bots in all our cases, the comparison shows that the three approaches produce very different results. We discuss why neither manual validation nor triangulation resolves the basic problems, and conclude that social scientists studying the influence of social bots on (political) communication and discourse dynamics should be careful with easy-to-use methods, and consider interdisciplinary research.
- ItemBRAT Rapid Annotation Tool(2022) Strippel, Christian; Laugwitz, Laura; Paasch-Colberg, Sünje; Esau, Katharina; Heft, AnnettIn the context of interdisciplinary collaboration, especially with colleagues from computer science, communication and media research has for some time been confronted with a wide range of research software with which it has had little prior experience. In addition to programming languages such as Python or R, these include specific tools for text analysis that represent an alternative to previous variants of computer-assisted content analysis. With the brat rapid annotation tool (BRAT) we present such an alternative in this paper and review it against the background of our experience in using it. BRAT is a web-based open-source text annotation tool that was developed by an international team of computer scientists about ten years ago. The article introduces the tool and its most important features, presents examples for its use in qualitative and quantitative content analyses on the basis of three case studies, and finally evaluates it with regard to potentials and difficulties for the field.
- ItemCan Fighting Misinformation Have a Negative Spillover Effect? How Warnings for the Threat of Misinformation Can Decrease General News Credibility(2023) Van Der Meer, Toni G. L. A.; Hameleers, Michael; Ohme, Jakob
- ItemCan Intergroup Contact in Virtual Reality (VR) Reduce Stigmatization Against People with Schizophrenia?(2021) Stelzmann, Daniela; Toth, Roland; Schieferdecker, David