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Digital technologies offer new communicative affordances to fight corruption. Bottom-up efforts increasingly use algorithmic tools, i.e., bots, to automate corruption reporting on social media platforms. This study investigates how to design a bot to effectively and responsibly mobilize people for collective action against corruption. In a large (n=1,331) pre-registered choice-based conjoint survey, we test six message design features: type of injustice, degree of injustice, anger, political partisanship, gender, and efficacy cues. Our results show that calling out cases of severe corruption mobilized people against corruption effectively. We find no empirical support for in-group favoritism based on political affiliation and gender. Yet, some commonly used design features can have contrasting effects on different audiences. We call for more social science research accompanying the technical development of algorithmic tools to fight corruption.

Corruption presents one of the biggest challenges of our time, and much hope is placed in artificial intelligence (AI) to combat it. Although the growing number of AI-based anti-corruption tools (AI-ACT) have been summarized, a critical examination of their promises and perils is lacking. Here we argue that the success of AI-ACT strongly depends on whether they are implemented top–down (by governments) or bottom–up (by citizens, non-governmental organizations or journalists). Top–down use of AI-ACT can consolidate power structures and thereby pose new corruption risks. Bottom–up use of AI-ACT has the potential to provide unprecedented means for the citizenry to keep their government and bureaucratic officials in check. We outline the societal and technical challenges that need to be overcome to harness the potential for AI to fight corruption.

Despite the immense societal importance of ethically designing artificial intelligence, little research on the public perceptions of ethical artificial intelligence principles exists. This becomes even more striking when considering that ethical artificial intelligence development has the aim to be human-centric and of benefit for the whole society. In this study, we investigate how ethical principles (explainability, fairness, security, accountability, accuracy, privacy, and machine autonomy) are weighted in comparison to each other. This is especially important, since simultaneously considering ethical principles is not only costly, but sometimes even impossible, as developers must make specific trade-off decisions. In this paper, we give first answers on the relative importance of ethical principles given a specific use case—the use of artificial intelligence in tax fraud detection. The results of a large conjoint survey ([Formula: see text]) suggest that, by and large, German respondents evaluate the ethical principles as equally important. However, subsequent cluster analysis shows that different preference models for ethically designed systems exist among the German population. These clusters substantially differ not only in the preferred ethical principles but also in the importance levels of the principles themselves. We further describe how these groups are constituted in terms of sociodemographics as well as opinions on artificial intelligence. Societal implications, as well as design challenges, are discussed.

The collection of Big Data and surging artificial intelligence (AI) technologies to analyze these data increasingly enable health insurers to calculate the individual health risks of their customers. By offering individualized rates, data-driven health insurance (HI) challenges fundamental norms of solidarity in universal healthcare systems. This paper investigates to what extent personal financial benefits of individualized HI, the associated privacy costs of mandatory data disclosure, and attitudinal healthcare solidarity affect people’s intention to switch to an individualized HI rate. Three pre-registered experiments with German respondents (Study 1: n = 162, Study 2: n = 439, Study 3: n = 1,621) suggest that financial incentives are highly effective in persuading citizens to switch to an individualized HI rate. The personal costs and people’s attitudinal healthcare solidarity do not moderate this positive relationship. As technological and demographic developments pressure current universal healthcare systems, the results raise important questions concerning the future of HI in increasingly digitalized societies and provide novel insights for healthcare practitioners, policy-makers, and researchers.

Covering sport mega events is a pivotal strategy for public service broadcasting (PSB) to claim audience support and public legitimacy. However, these mega events are subject to considerable controversy due to their association with doping or corruption. This raises the question for the PSB of how to satisfy the audience of the Olympic Games: by looking closely or by looking away? Conducting two empirical studies, this article investigates how German public service broadcasters reported the sociopolitical problems related to the 2016 Olympic Summer Games and whether the coverage has met the expectations of the audience. The results of a content analysis suggest that a substantial amount of coverage was dedicated to the problematic aspects of the Games. A conjoint analysis shows that German public service broadcasters did not meet the expectations of different audience segments: Neither the core audience nor event-driven spectators and certainly not the outsiders of media sports were fully satisfied by the Olympic program menu of German PSB.

The implementation of financial institutions such as the European Stability Mechanism (ESM) in light of the European debt crisis has sparked a hitherto unknown redistribution of financial resources among EU member states without guarantees that this debt will be repaid. Thus, the concept of European solidarity has gained momentum during the crisis. This chapter unpacks the political, legal and social implications of the ESM and sheds light on the related challenges for European solidarity on the macro and the micro-level.

This book explores the processes through which European solidarity is constructed. More specifically, it investigates how the media's framing of European identity can facilitate and/or impede the emergence of European solidarity on the individual level. Through an online experiment that tested the effect of two different media identity frames on individual solidarity during the European debt crisis, the author argues that the exposure to news articles using a value-based identity frame boosts solidarity compared to an economic identity frame.This interdisciplinary work will be of interest to scholars of political sociology, political communication and political psychology, as well as any researchers who study European integration.

This chapter explores the concept of media identity framing. For that, the main reasoning of the framing approach will be outlined by distinguishing between (1) strategic frames, (2) media frames and (3) cognitive frames. Identity frames refer to strategic frames that suggest a specific interpretation of the content of European identity, e.g. an economic community vs. a community of common values. Furthermore, as this study investigates the effects of frames, the process model by Scheufele (1999) will be applied to media identity framing about the EU. To that end, the chapter explains the following three stages of framing effects: (1) identity frame building, (2) identity frame setting, (3) individual-level effects of identity framing.

This chapter synthesises the arguments developed in the previous chapters. To that end, it derives a moderated serial-mediation model running from exposure to identity frames through perceived importance of identity frames and attitudinal European solidarity to behavioural European solidarity. The serial-mediation is expected to be moderated by perceived benefits for Germany.

This chapter thoroughly reviews the existing theoretical and empirical literature on (European) solidarity and derives a norm-based concept of individual European solidarity that distinguishes between (1) different levels (macro & micro), (2) different dimensions (attitudinal & behavioural) and (3) different types (collective good situations, sharing situations, need situations, loyalty situations). Moreover, the chapter draws upon empirical evidence to identify pivotal drivers of individual European solidarity, most notably European identity.

This chapter outlines the methodology used to test the hypotheses: a single-exposure online experiment with 1611 German respondents. It first outlines how the variables were measured and introduces the pre-testing procedure as well as the power analysis. After elaborating on the fieldwork, the filtering process and the final sample, the chapter closes with a description of the strategy used to analyse the expected moderated serial-mediation effect.

This chapter sheds light on European identity by conceptually distinguishing between social identity (identity of individuals) and collective identity (identity of groups). At the individual level, the chapter addresses the key question of how strongly EU citizens identify as Europeans (intensity of European identity) and further argues that European identity always refers to specific social representations or identity frames coexisting in the minds of European citizens (content of European identity). At the collective level, the chapter links the literature on European identity with the literature on European public spheres and argues that the construction of collective European identity takes place in public discourses. The intensity of collective identity refers to the degree of Europeanisation of national public spheres as well as identity claims within the discourse. The content of collective identity can be conceived through identity frames existing in the media discourse.

Political communication via social media might well counter the eroding political trust. In particular, social networking sites (SNS) enable direct flows of communication between citizens and the political elite, thereby reducing social and political gaps. Based on the concept of personalization of politics, we argue that interactions with politicians on SNS affect trust in government through a two-step process: First, interactions on SNS make citizens evaluate politicians’ characters more favorably. Second, these evaluations serve as cues for the citizens to develop or withdraw trust in government. We test indirect effects using four character traits as mediators: leadership, benevolence, responsiveness, and likeability. A representative online survey ( n = 1117; in Germany) reveals that interactions with politicians on SNS increase the perceived likeability of candidates, and thus also trust in government. However, they do not affect the evaluation of the other traits: leadership, benevolence, and responsiveness.

Algorithmic decision-making (ADM) is becoming increasingly important in all areas of social life. In higher education, machine-learning systems have manifold uses because they can efficiently process large amounts of student data and use these data to arrive at effective decisions. Despite the potential upsides of ADM systems, fairness concerns are gaining momentum in academic and public discourses. The criticism largely focuses on the disparate effects of ADM. That is, algorithms may not serve as objective and fair decision-makers but, rather, reproduce biases existing within the respective training data. This study adopted a different approach by focusing on individual perceptions of fairness. Specifically, we looked at two different dimensions of perceived fairness: (i) procedural fairness and (ii) distributive fairness. Using cross-sectional survey data (n = 304) from a large German university, we tested whether students' assessments of fairness differ with respect to algorithmic vs. human decision-making (HDM) within the higher education context. Furthermore, we investigated whether fairness perceptions have subsequent effects on three different outcome variables, which are hugely important for universities: (1) exit, (2) voice, and (3) organizational reputation. The results of our survey suggest that participants evaluated ADM higher than HDM in terms of both procedural and distributive fairness. Concerning the subsequent effects of fairness perceptions, we find that (1) distributive fairness as well as procedural fairness perceptions have a negative impact on the intention to protest against an ADM system, whereas (2) only procedural fairness perceptions negatively affect the likelihood of exiting. Finally, (3) distributive fairness, but not procedural fairness perceptions have a positive effect on organizational reputation. For universities aiming to implement ADM systems, it is crucial, therefore, to take possible fairness issues and their further implications into account.

The notion of the ‘face effect’ in political communication denotes a process by which people spontaneously infer the personal character traits of political candidates (e.g., competence, attractiveness) from campaign portrait photographs and election posters. Previous research has shown that those spontaneous trait inferences (STIs) affect people’s voting decisions. Combining survey responses, election results from official statistics, and aggregate data, the present study demonstrates that STIs of competence, attractiveness, and leadership help to predict the outcome of direct election in Germany. Furthermore, results suggest that even when controlled for context variables, judgments about a candidate’s competence solely derived from his or her face are connected to the difference in vote shares between the winning candidate and the runner-up. Effects are particularly strong when newcomers compete against each other.

In recent years, sport mega events have been frequently awarded to autocratic countries whose regimes violate democratic values and human rights. Based on the theory of cognitive dissonance, we assume that this is a potential source of internal conflict for viewers, especially for sports enthusiasts and politically aware recipients. Special attention rests on the consequences of the recipients’ strategies of addressing this predicament for important stakeholders of these events, namely the reporting media, the host country and sponsors. We conducted an online survey among 711 German respondents to examine how recipients cope with this dilemma using the forthcoming FIFA soccer World Cup 2018 in Russia as an example. Our results show that while recipients are strongly interested in soccer and politics, most of them do not necessarily perceive these two spheres as inextricably connected. Their awareness of sociopolitical issues in the context of sport events—and thus the decisive factor to explain cognitive dissonance—is arguably low. Still, when recipients experience cognitive dissonance they rely on certain strategies to reduce or avoid dissonance. They do not elude this dilemma by preferring sports broadcasting without coverage of the event’s negative circumstances, but are actually willing to pass on parts of the tournament. They also do not denigrate the credibility of the media or emphasize positive aspects of the host country Russia. In fact, the recipients would prefer if the World Cup had not been awarded to Russia in the first place. However, respondents experiencing cognitive dissonance are also more likely to engage in political consumerism, by deliberately deciding against or in favor of products and sponsors depending on whether or not those are associated with the event.

In modern democracies, trust in government is a key indicator of political legitimacy and stability. Drawing from theories of media effects, we investigated whether using traditional media has a negative (media malaise hypothesis) or a positive (virtuous circle hypothesis) impact on trust in the national government. We used a serial mediation model involving evaluations of politicians and evaluations of the political process as mediators of how political communications influence trust in government. To test the model empirically, we conducted an online survey among 1 115 respondents in Germany. Results suggest that the use of traditional media to access political information has a direct positive impact on trust in government mediated by people’s evaluations of politicians and of the political process. We also found a positive serial mediation effect of using traditional media on trust in government mediated first by evaluations of politicians and second by evaluations of the political process.

Governmental intervention in credit markets typically involves the allocation of credit in the light of market failures. In this paper we evaluate federal lending programs while presuming positive externalities and symmetrically informed market participants. For common objectives of governmental lending institutions we verify that optimal lending structures require the application of the gap lender principle. We also show that lending programs can never be selffinancing, due to the positive subsidy margin. Within this general framework, we contrast the policies of the US SBA and the German KfW and show that neither institution features an optimal lending structure., Working papers series, ISSN 2628-1724, 2006, Heft 19