Today’s high-choice media environment offers various opportunities for interest-driven news exposure, resulting in highly diverse and fragmented news usage patterns, especially in the digital media environment. Media repertoires provide a suitable theoretical framework for considering these circumstances and investigating the entirety and interrelatedness of individuals’ news sources, rather than focusing on singular news offerings. We explore media repertoires focusing on news by relying on behavioral tracking data from 805 German respondents over eleven weeks (November 2022–January 2023). Conducting a latent class analysis based on news usage frequencies across seventeen news categories, we identified eight digital news media repertoires with distinct usage patterns. Repertoire comparisons via analysis of variance (ANOVA) further revealed differences in the news topics used, users’ diversity of news outlets, news concentration, and news usage duration. Implications for future research on investigating media repertoire compositions are discussed.
This paper investigates how AI narratives actively constrain the horizon of conceivable governance options. Moving beyond the established finding that narratives influence policy, we argue they fundamentally prefigure the scope of the politically thinkable by creating what we term “Policy Umwelten.” Adapting Jakob von Uexküll’s concept, a Policy Umwelt describes the perceptible and actionable landscape of interventions available within a given narrative, which systematically renders alternatives invisible. We analyze three competing narratives: Existential Risk, Accelerationism, and Critical AI. We do so through a “What’s the Problem Represented to Be?” analysis of their foundational manifestos. Each constructs a distinct Umwelt: Existential Risk makes global technocratic containment imperative; Accelerationism legitimizes only deregulation and market liberation; and Critical AI centers structural reform. Despite their overt conflict, these narratives converge in constructing Policy Umwelten that render a pragmatic approach to governance difficult to perceive: one that emphasizes iterative learning from empirical feedback and institutional flexibility over grand visions or predetermined certainties. The paper concludes that the most significant constraint on AI policy is not a lack of options but a collective failure of political perception. The Policy Umwelt concept thus provides a diagnostic tool for mapping ideological deadlock and identifying pathways toward more adaptive and less deterministic technological futures.
Despite the widespread assumption that trust in news media drives news use, empirical research consistently finds only a modest correlation between the two. This study investigates possible explanations for the modest relationship between news media trust and use, drawing on recent qualitative insights and testing five hypotheses using a four-wave panel survey of Swedish respondents ( N = 3,542). We examine whether outlet-specific trust better predicts news use than generalized media trust, and whether the tendency for selective exposure, news avoidance, news finds me (NFM) perceptions, and conspiracy mindset moderate the trust–exposure relationship. Contrary to expectations, outlet-specific trust did not outperform generalized trust in predicting news use. Selective exposure showed no significant moderating effects. In contrast, news avoidance significantly moderated the relationship, such that the association between news media trust and mainstream news media use was stronger for those reporting low intentions to avoid the news. Stronger associations were also observed for those ranking themselves high on the NFM and conspirancy mindset scales, though these latter interactions became insignificant when entering all interactions to the model simulteneously.
This study compares the guiding influence of political attitudes and emotions on citizens’ news selection within a fragmented, polarized, and emotionalized political information environment. While selective exposure has long been a central focus in research on political information behavior, the guiding role of emotions has received far less attention. This study brings both perspectives together by directly comparing how pre-existing attitudes and momentary emotional responses shape citizens’ news choices. Using migration as a salient and contested issue, an online experiment conducted in Germany in June 2025 ( N = 1,002) tested how framing variations in political stance (supportive, balanced, opposing migration) and emotional valence (positive, unemotional, negative) shape citizens’ news choices, and how these effects depend on individuals’ pre-existing attitudes and induced emotional responses toward migration. Results reveal a clear negativity bias: negatively valenced and contra-migration news were chosen most frequently, whereas positive and pro-migration ones were least preferred. Negative affect increased the likelihood of selecting negatively framed news, while positive affect showed no effect. In contrast, pre-existing attitudes exerted stronger and more consistent guidance, as citizens predominantly selected attitude-congruent information. The findings highlight how affective and cognitive orientations jointly shape selective exposure and suggest possible implications for how such patterns may unfold in algorithmically curated political information environments.
The integration of generative artificial intelligence (GenAI) in newsrooms has prompted scholarly examination of its ethical use. While research has examined journalists’ ethical practices and news audiences’ perceptions, few studies have examined the perceptions of other key stakeholders (e.g., journalism educators, policymakers, influencers, and information technology experts) whose perceptions may influence ethical adoption. Rooted in folk theories as an explanatory and normative framework for making sense of complex phenomena, we interviewed 94 stakeholders to examine their folk theories about GenAI and their ethical understanding of its use in Kenyan journalism. Findings show that across stakeholder groups, participants’ folk theories of what GenAI “is” shape how they interpret ethical concerns and perceive its potential consequences for journalism. Specifically, viewing GenAI as a content-creation tool connects to concerns about laziness, de-skilling, plagiarism, and the erosion of journalists’ professional standards, as the technology risks replacing human creativity. Framing GenAI as a data-driven or algorithmic system aligns with concerns about misinformation, bias, and stereotypes against Kenyans stemming from Western data dominance. Understanding GenAI as a human-like partner fosters fear about blurred boundaries around authorship, transparency, and responsibility in newsrooms. Stakeholders’ folk theories are further rooted in their professional identities and relationships to GenAI. Our findings contribute to scholarship on GenAI ethics by underscoring the importance of expanding journalism scholarship to account for stakeholders’ perceptions.
This study provides a theoretical framework for the dynamic interactions between media systems and violent conflict. Taking the media system framework developed by Hallin and Mancini in Comparing Media Systems: Three Models of Media and Politics as a point of departure, the study highlights the role of violent conflict in transforming media systems beyond the Western world. To achieve this goal, the study first refines the media system framework to make it applicable to non-Western countries affected by violent conflict. It conceptualizes violent conflict as a social transformative force that alters political and media systems. Building on these steps, we present a theoretical framework for the mechanism by which violent conflicts transform political and media systems. The theoretical framework is then utilized to study these transformation processes in four purposefully sampled countries: Afghanistan, Lebanon, Israel, and Turkey. Finally, the four countries are used as case studies to discern three patterns of interaction between violent conflict and political and media systems. The results show three patterns: victorious autocrat, stalemate, and instrumental escalation. This study contributes to the literature on media systems and the relationship between the media and violent conflict.
Campaign language in the United States has grown markedly polarized, with candidates increasingly speaking in party-distinctive ways. Yet the mechanisms driving this linguistic divergence remain insufficiently understood. This study proposes identity-policy fusion, a framing strategy in which candidates embed distinctive biographical vocabulary into policy statements, as one factor shaping this divergence. By framing policy as an authentic extension of lived experience, fusion may tie stances to in-group identity and biographical authority, raising the psychological and social costs of disagreement. Using computational text analysis of 41,842 policy statements from 3,343 U.S. House candidates in the 2018, 2020, and 2022 election cycles, the study operationalizes fusion as term frequency-inverse document frequency (TF-IDF)-weighted lexical overlap between biographies and policy texts, and polarization as a statement's relative similarity to in-party versus out-party linguistic norms within policy domains. Ordinary least squares regression shows that fusion is significantly associated with higher polarization in campaign language, with the association approximately 26 percent stronger for Republicans than Democrats. This partisan asymmetry is consistent with fusion serving as an alternative source of legitimation under conditions of contested institutional authority, illuminating a potential mechanism through which elite messaging may harden partisan boundaries.
The rise of right-wing alternative media across many Western democracies has been discussed as a challenge to democratic institutions and processes, contributing to the erosion of political trust. Political trust scholars, as well as previous research on alternative media use, have both recognized that emotions play a crucial role in their subject of study. However, research investigating this affective component is extremely sparse. Drawing from appraisal theory and affective intelligence theory, this study investigates the role of anger and anxiety in the nexus between right-wing alternative media use and political trust. The study relies on data from a three-wave panel survey conducted in Austria ( N = 1,504) to estimate a random intercept cross-lagged panel model distinguishing within- and between-person relationships. Results suggest that right-wing alternative media use increased political anger over time. Further, anger reduced political trust over time. For anxiety, the picture is more nuanced: Political anxiety was not affected by right-wing alternative media use. Anxiety reduced political trust between wave 1 and wave 2, but not between wave 2 and wave 3. Neither anger nor anxiety increased right-wing alternative media use over time. Implications are discussed.
Public service media (PSM) face a democratic dilemma when covering right-wing populism: They are expected to be impartial and ensure pluralism in their reporting. This requires them to give visibility to a range of views, including those of far-right parties, while safeguarding democratic principles such as non-discrimination and human dignity. In this context, it is essential to understand how PSM representatives reflect on their reporting of right-wing populism. Drawing on the concept of journalistic roles, this study examines PSM representatives' narrated role performance and role orientation in reporting on populism. Based on semi-structured interviews with twenty-six German PSM representatives, the findings reveal that journalists perceive past reporting mistakes and partly believe that PSM have contributed to the rise of populism. Regarding their role orientation, PSM representatives emphasize that they do not wish to exclude populist actors from coverage unless they make anti-constitutional statements, a stance they justify by the democratic election of these figures. More broadly, PSM representatives take on three distinct role orientations when reporting on populism: as disseminators, they aim to provide neutral coverage of events; as watchdogs, they seek to critically scrutinize populist actors; and as educators, they strive to inform the public about problematic developments within populist parties. Against the backdrop of the growing support for the German populist party Alternative f & uuml;r Deutschland (AfD), this study contributes to existing research by proposing a conceptual framework for reporting on populism and offering qualitative insights into how PSM representatives navigate their role in covering the AfD.
Ethical approaches to address media harm and build more idealized relationships between journalists and marginalized communities have relied heavily on prescriptions for unidirectional journalistic practices, often framed as an ethic of care . In this exploration of relationship development and maintenance through the perspectives of trusted journalists, we identify practices and exchanges that reflect a more reciprocal framework of an ethic of love . We present a case study derived from interviews with seventeen journalists named as trusted by Black community members in Minneapolis, Minnesota, where police murdered George Floyd in 2020. His murder reignited an international movement to address police brutality and systemic racism. Results show that communities and journalists rely on each other to achieve healthy relationships and exchanges. These relationships require both mutual agency and reciprocity, and many dimensions of their exchanges align with Black feminist scholar bell hooks’ ethic of love. Trusted journalists successfully addressed historic media harm through two prominent practices identified in this study: diligence and deference. Findings call upon scholars to craft a more inclusive and internationally relevant understanding of journalistic strategies that repair historic harms by centering vulnerable communities—for the ultimate benefit of all communities. Drawing on design justice principles, which posit that centering the most vulnerable communities creates more inclusive and universal systems, we discuss how the ethic of love framework can strengthen information pathways between journalists and communities.
As generative artificial intelligence (AI) reshapes news production, understanding what drives global audiences to accept AI-generated news is critical. Existing research largely adopts a competence-based perspective, neglecting the complex role of trust dimensions and macro-political contexts. This study examines how AI self-efficacy interacts with two distinct dimensions of trust (competence trust and ethical trust) to shape acceptance of AI-generated news, and how these relationships vary across political environments. Analyzing survey data from 24,000 respondents across twenty-four countries, we find that ethical trust is a substantially stronger predictor of acceptance than competence trust, while AI self-efficacy promotes acceptance only when ethical trust is high. Multilevel analysis incorporating national-level indicators (press freedom, regime type, and AI readiness) reveals that the relationship between ethical trust and acceptance is stronger in open, liberal democratic, and technologically ready societies. These findings suggest that the legitimacy of AI-generated news is more strongly associated with audiences’ ethical evaluations of AI systems than with perceived technical capability, and that this association is shaped by the normative expectations that different political contexts cultivate.
As generative AI becomes increasingly integrated into journalism, questions about its implications for journalistic practice grow more urgent. Despite the rise of AI systems, news organizations often lack an informed understanding of how these systems operate, potentially undermining journalists' capacity to exercise agency in AI-assisted news production. This study explores how large language models (LLMs), such as ChatGPT, can reflect journalistic value systems. It does this by prompting the GPT-4o model to respond to survey items from the Worlds of Journalism Study that measure journalistic role perceptions, epistemologies, and ethics. These responses were compared to actual survey data from the US, UK, and Germany. Our findings suggest that GPT-4o's outputs correspond most strongly to the survey responses of politically centrist, full-time journalists whose employers have a TV background, while showing less alignment with right-leaning, part-time, and non-degree-holding journalists. These propensities were most pronounced in the German dataset. While we do not assert that GPT-4o's cultural orientation directly translates to its journalistic applications, the results reveal which groups of journalists' perspectives the LLM is more-or less-likely to reflect. By mapping this alignment, the study offers an empirical point of departure for guiding how journalists can maintain agency in their use of LLMs, and thereby contributes to ongoing discourse about the ethical, epistemological, and institutional dimensions of AI in journalism.
This article examines how journalists respond to restrictions and the dismantling of spaces essential to their professional and social lives by creating alternative work and social interaction environments. It focuses on Kashmir, where, following the revocation of the region's semi-autonomy in 2019, several journalists and news organisations were forced to vacate their offices and shared spaces central to journalistic life were shut down. These developments not only disrupted daily routines and professional practices but also fractured the connections and associations once sustained through communal settings such as the Press Enclave and former Kashmir Press Club, which was controversially closed in 2021. Drawing on ethnographic interviews and participant observation, the article explores how journalists have responded to these constraints by cultivating independent workspaces and engaging in social and cultural practices that help maintain both their professional commitments and their sense of community. It shows that journalists in Kashmir have adopted adaptive strategies that allow them to continue reporting and remain connected with peers. These include forming informal community workspaces and participating in everyday social rituals that take place in public spaces. The article argues that these spaces and practices, though outside formal news institutions, play a critical role in sustaining journalism under pressure. By focusing on how journalists negotiate their environment, the study contributes to wider discussions on journalism and space, highlighting the ongoing importance of physical proximity, social networks, and collective resilience in maintaining independent journalism in politically repressive conditions.
As generative AI technologies reshape the landscape of political communication, they are increasingly used to craft symbolic narratives of international rivalry. This study investigates how AI-generated political parodies circulating in Chinese digital spaces function as affective tools of "simulated superiority," helping public process geopolitical tension and reassert national identity. Based on a between-subjects experiment (N = 397) conducted during the 2025 U.S.-China tariff dispute, we find that exposure to AI-generated political parody increases feelings of collective superiority and reduces aggressive attitudes toward the United States, while reductions in perceived geopolitical threat emerge primarily under conditions of high perceived visual realism. Theoretically, we extend classical superiority theory by highlighting three core features of generative parody-de-authorship, narrative re-imagination, and perceived visual realism-as mechanisms of affective political expression. Our findings suggest that AI-generated satire can mediate geopolitical emotions and shape symbolic boundaries of competition and belonging, offering new insight into how technologically produced content influences global political imaginaries and mediated public sentiment.
This paper analyzes the discursive dynamics of mediated truth contestation by examining how assertions of truthfulness and references to falsehood are constructed in Austrian and Czech news coverage of migration. Employing automated content analysis on an extensive dataset of 162,943 news articles (2013-2019), we apply latent semantic scaling to assess differences between tabloid and broadsheet newspapers and between mainstream and alternative news media, investigating how media formats and media types shape the discursive construction of truthfulness and falsehoods in news articles. We further use named entity recognition techniques to examine the role of populist politicians, government representatives, and EU actors in mediated truth contestation, and consider cross-national differences to investigate how political contexts influence these dynamics. By integrating insights from political communication and computational text analysis, this study contributes to debates on post-truth politics, media polarization, and the strategic use of truth and lies in democratic discourse.
"Wolf Warrior Diplomacy," characterized by its assertive and confrontational tone, marks a significant shift in China's international communication strategy. While it has attracted global attention, emerging evidence suggests that its aggressive rhetoric may be counterproductive, alienating democratic publics. This study investigates the impact of "Wolf Warrior Diplomacy" in Japan, South Korea, and Taiwan-three East Asian democracies with complex relationships with China that have been underexplored as targets of this strategy. In a preregistered online experiment conducted in each country, participants were randomly assigned to view either neutral content or posts that aggressively emphasized China's superiority over the United States. The results indicate that exposure to "Wolf Warrior" messaging produces modest but statistically detectable declines in several China-directed evaluations across the three countries, with the largest and most consistent attitudinal shifts in South Korea. Although some negative effects on perceptions of the United States were observed, these were sporadic and inconsistent. Support for democratic values remained largely unchanged, and participants exhibited a low willingness to share "Wolf Warrior" messages on social media, limiting the strategy's potential for broader dissemination. Overall, China's combative diplomatic messaging appears not only ineffective but also potentially counterproductive in shaping public opinion in East Asian democracies, offering important implications for political communication and the limits of authoritarian soft power.
Recent scholarship has aimed to expand the concept of political scandal by examining problematic statements made by public figures, often termed "talk scandals." However, a major limitation of existing studies is the lack of clear differentiation between gaffes and talk scandals. This study aims to better understand talk scandals by focusing on the political dynamics, including the relationship between the media and politics, that generate them. Using a new collection of political gaffes, we examine the frequency of gaffes associated with different cabinet positions, the locations of gaffes, the durations of gaffes, and the major societal actors who expressed offense at statements made by Japanese cabinet ministers. Through quantitative analysis and case studies, we explore why problematic statements escalate into scandals while others quickly fade from public attention. Our analysis suggests that the news media alone cannot independently transform a gaffe into a talk scandal. Instead, journalists must reference and justify their coverage by citing clear criticisms from offended groups or individuals. These statements tend to develop into talk scandals only when they receive strong and sustained criticism within the political arena.
