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A Democratic Approach to Digital Rights: Comparing Perspectives on Digital Sovereignty on the City Level
(2023) Pierri, Paola; Calderón Lüning, Elizabeth
This 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.
A Pandemic of Prediction. On the Circulation of Contagion Models between Public Health and Public Safety
(2021) Heimstädt, Maximilian; Egbert, Simon; Esposito, Elena
Digital 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.
A review of technologies for collaborative online information seeking. On the contribution of collaborative argumentation
(2021) Mayweg-Paus, Elisabeth; Zimmermann, Maria; Le, Nguyen-Thinh; Pinkwart, Niels
In 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.
Active 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
Active use of social networking sites (SNSs) has long been assumed to benefit users’ well-being. However, this established hypothesis is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with considerable heterogeneity among existing studies on the hypothesis and causal evidence still limited, a final verdict on its robustness is still pending. To contribute to this ongoing debate, we conducted a week-long randomized control trial with N = 381 adult Instagram users recruited via Prolific. Specifically, we tested how active SNS use, operationalized as picture postings on Instagram, affects different dimensions of well-being. The results depicted a positive effect on users’ positive affect but null findings for other well-being outcomes. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs.
Algorithmic Governance
(2019) Katzenbach, Christian; Ulbricht, Lena
Algorithmic governance as a key concept in controversies around the emerging digital society highlights the idea that digital technologies produce social ordering in a specific way. Starting with the origins of the concept, this paper portrays different perspectives and objects of inquiry where algorithmic governance has gained prominence ranging from the public sector to labour management and ordering digital communication. Recurrent controversies across all sectors such as datafication and surveillance, bias, agency and transparency indicate that the concept of algorithmic governance allows to bring objects of inquiry and research fields that had not been related before into a joint conversation. Short case studies on predictive policy and automated content moderation show that algorithmic governance is multiple, contingent and contested. It takes different forms in different contexts and jurisdictions, and it is shaped by interests, power, and resistance.
Algorithmic 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
Algorithmic regulation. A maturing concept for investigating regulation of and through algorithms
(2022) Ulbricht, Lena; Yeung, Karen
This 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.
An uncertain elite: Professional differences and similarities between engineers and tech workers in times of digital transformation
(2025) Krzywdzinski, Martin; Pfeiffer, Sabine; Kuhlmann, Martin; Ottaiano, Mario; Heinlein, Michael; Ritter, Tobias; Neumer, Judith; Huchler, Norbert
The digital transformation of industries has given rise to new categories of tech workers, such as software engineers and UX/UI designers, who now work alongside traditional engineers. This study explores the evolving relationship between these groups, focusing on work processes, status perceptions and professional interactions. The research questions addressed include: how has digitalisation affected these two groups’ work processes? what strategies do they use to maintain or improve their career paths? and how do their roles converge or diverge? Using qualitative data from interviews and workshops in a German automotive company undergoing a digital and electric mobility transformation, the study finds both competition and cooperation between engineers and IT professionals, with the former adopting some IT work methods and the latter adjusting to the highly structured processes of the industrial sector. Despite growing overlaps, distinct professional identities nevertheless remain.
Anti‐elitism in the European Radical Right in Comparative Perspective
(2023) Vaughan, Michael; Heft, Annett
To 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.
Anything 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.
Are 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
Relating to theories of dissonant public spheres and affective publics, we study negativity, dramatization, and populist content in political party Facebook posts across 12 countries during the 2014 and 2019 European Parliament Election campaigns. A quantitative content analysis of 14,293 posts from 111 (2014) and 116 (2019) political parties shows that negative emotion, negative campaigning, dramatization, and populist content has increased over this time. We show that political parties sought to evoke more negative emotions and generate more dramatization, engaged more in negative campaigning, and included more populist content in their Facebook posts in the 2019 EP election than in 2014. Further, we show that posts evoking negative emotions and dramatization and involving negative campaigning yield higher user engagement than other posts, while populist content also led to more user reactions in 2014, but not in 2019. Negative, exaggerated, and sensationalized messaging therefore makes sense from a strategic perspective, because the increased frequencies of likes, shares, and comments make parties’ messages travel farther and deeper in social networks, thereby reaching a wider audience. It seems that the rise in affective and dissonant communication has not emerged unintentionally, but is also a result of strategic campaigning.
Articulation Work and Tinkering for Fairness in Machine Learning
(2024) Fahimi, Miriam; Russo, Mayra; Scott, Kristen M.; Vidal, Maria-Esther; Berendt, Bettina; Kinder-Kurlanda, Katharina
The field of fair AI aims to counter biased algorithms through computational modelling. However, it faces increasing criticism for perpetuating the use of overly technical and reductionist methods. As a result, novel approaches appear in the field to address more socially-oriented and interdisciplinary (SOI) perspectives on fair AI. In this paper, we take this dynamic as the starting point to study the tension between computer science (CS) and SOI research. By drawing on STS and CSCW theory, we position fair AI research as a matter of 'organizational alignment': what makes research 'doable' is the successful alignment of three levels of work organization (the social world, the laboratory, and the experiment). Based on qualitative interviews with CS researchers, we analyze the tasks, resources, and actors required for doable research in the case of fair AI. We find that CS researchers engage with SOI research to some extent, but organizational conditions, articulation work, and ambiguities of the social world constrain the doability of SOI research for them. Based on our findings, we identify and discuss problems for aligning CS and SOI as fair AI continues to evolve.
Audit - and then what? A roadmap for digitization of learning factories
(2019) Ullrich, André; Enke, Judith; Teichmann, Malte; Kreß, Antonio; Gronau, Norbert
Current 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.
Avoiding 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
Lower levels of news use are generally understood to be associated with less political engagement among citizens. But while some people simply have a low preference for news, others avoid the news intentionally. So far little is known about the relationship between active news avoidance and civic engagement in society, a void this study has set out to fill. Based on a four-wave general population panel survey in the Netherlands, conducted between April and July 2020 (N = 1,084) during a crisis situation, this research-in-brief investigates the development of news avoidance and pro-social civic engagement over time. Results suggest that higher news topic avoidance results in higher levels of civic engagement. The study discusses different explanations for why less news can mean more engagement.
Beyond “Industry 4.0”. B2B factory networks as an alternative path towards the digital transformation of manufacturing and work
(2021) Butollo, Florian; Schneidemesser, Lea
This 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.
Bias 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, Steffen
Artificial 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.
Bot, or not? Comparing three methods for detecting social bots in five political discourses
(2021) Martini, Franziska; Samula, Paul; Keller, Tobias R; Klinger, Ulrike
Social 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.
BRAT Rapid Annotation Tool
(2022) Strippel, Christian; Laugwitz, Laura; Paasch-Colberg, Sünje; Esau, Katharina; Heft, Annett
In 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.
Can 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
In the battle against misinformation, do negative spillover effects of communicative efforts intended to protect audiences from inaccurate information exist? Given the relatively limited prevalence of misinformation in people’s news diets, this study explores if the heightened salience of misinformation as a persistent societal threat can have an unintended spillover effect by decreasing the credibility of factually accurate news. Using an experimental design (N = 1305), we test whether credibility ratings of factually accurate news are subject to exposure to misinformation, corrective information, misinformation warnings, and news media literacy (NML) interventions relativizing the misinformation threat. Findings suggest that efforts like warning about the threat of misinformation can prime general distrust in authentic news, hinting toward a deception bias in the context of fear of misinformation being salient. Next, the successfulness of NML interventions is not straight forward if it comes to avoiding that the salience of misinformation distorts people’s creditability accuracy. We conclude that the threats of the misinformation order may not just be remedied by fighting false information, but also by reestablishing trust in legitimate news.
Can Intergroup Contact in Virtual Reality (VR) Reduce Stigmatization Against People with Schizophrenia?
(2021) Stelzmann, Daniela; Toth, Roland; Schieferdecker, David
People with mental disorders such as schizophrenia do not only suffer from the symptoms of their disorders but also from the stigma attached to it. Although direct intergroup contact is an effective tool to reduce stigmatization, it is rare in real life and costly to be established in interventions, and the success of traditional media campaigns is debatable. We propose Virtual Reality (VR) as a low-threshold alternative for establishing contact since it involves less barriers for affected and unaffected persons. In a 2 + 1 experiment (n = 114), we compared the effects of encounters with a person with schizophrenia through a VR video with contact through a regular video and no contact at all on anxiety, empathy, social proximity, and benevolence towards people with schizophrenia. We found that contact via VR reduced stigmatization only for participants who liked the person encountered. Our data suggest that it is crucial how participants evaluate the person that they encounter and that stronger perception of spatial presence during reception plays an important role, too. Therefore, we discussvarious boundary conditions that need to be considered in VR interventions and future research on destigmatization towards mental disorders, especially schizophrenia.

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