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The current study provides a new level of empirical evidence for the nature of ethnic stereotypes in news content by drawing on a sample of more than 3 million Dutch news items. The study's findings demonstrate that universally accepted dimensions of stereotype content (i.e., low-status and high-threat attributes) can be replicated in news media content across a diverse set of ingroup and outgroup categories. Representations of minorities in newspapers have become progressively remote from factual integration outcomes, and are therefore rather an artifact of news production processes than a true reflection of what is actually happening in society.

AbstractChatbots have in recent years increasingly been used by organizations to interact with their customers. Interestingly, most of these chatbots are gendered as female, displaying stereotypical notions in their avatars, profile pictures and language. Considering the harmful effects associated with gender-based stereotyping at a societal level—and in particular the detrimental effects to women—it is crucial to understand the effects of such stereotyping when transferred and perpetuated by chatbots. The current study draws on the Stereotype Content Model (SCM) and explores how the warmth (high vs. low) of a chatbot's language and the chatbot's assigned gender elicit stereotypes that affect the perceived trust, helpfulness, and competence of the chatbot. In doing so, this study shows how established stereotype theory can be used as a framework for human-machine communication research. Moreover, its results can serve as a foundation to explore ways of mitigating the perpetuation of stereotyping and bring forward a broader discussion on ethical considerations for human-machine communication.

In the past decade, European governments have implemented activating policy reforms to maximize older workers' employment and employability, representing a paradigmatic change in approaches to work and retirement. This study isolates the factors that explain the relative success and failure of competitive frames that are either in favor of or against activating policies in European news coverage, by applying time-series analysis (ordinary least squares with panel-corrected standard errors) to monthly aggregated news coverage in the Netherlands, the United Kingdom, Denmark, and Spain over the timespan 2006–2013. The results show that pro-activating and counteractivating frames generally coincide in competitive framing environments. The pro-activating frame proliferated in times of high employment protection, whereas the counteractivating frame prevailed stronger in conservative compared with progressive newspapers, and gained momentum during the aftermath of the financial crisis and in times governments on the economic left were in power. The study advances knowledge of competitive issue framing by demonstrating how the economic, policy, and political context matters for the emergence and evolvement of competing frames. In addition, the findings contribute to the understanding of the factors that contribute to news representations that promote active aging in European news, which may foster support for policy reforms that sustain older workers' employability.

In the past decade, European governments have implemented activating policy reforms to maximize older workers' employment and employability, representing a paradigmatic change in approaches to work and retirement. This study isolates the factors that explain the relative success and failure of competitive frames that are either in favor of or against activating policies in European news coverage, by applying time-series analysis (ordinary least squares with panel-corrected standard errors) to monthly aggregated news coverage in the Netherlands, the United Kingdom, Denmark, and Spain over the timespan 2006–2013. The results show that pro-activating and counteractivating frames generally coincide in competitive framing environments. The pro-activating frame proliferated in times of high employment protection, whereas the counteractivating frame prevailed stronger in conservative compared with progressive newspapers, and gained momentum during the aftermath of the financial crisis and in times governments on the economic left were in power. The study advances knowledge of competitive issue framing by demonstrating how the economic, policy, and political context matters for the emergence and evolvement of competing frames. In addition, the findings contribute to the understanding of the factors that contribute to news representations that promote active aging in European news, which may foster support for policy reforms that sustain older workers' employability.

This study introduces the element of time to investigate the causal relation between organizational and news media agendas. Reciprocal time-series analyses were applied to daily-level aggregated press releases ( n = 17,221) and news articles ( n = 74,067). Results indicate that on the first level of agenda building, organizational and news agendas are intertwined in an intimate relation of reciprocal influence, in which organizations more often take the lead. Conversely, results suggest that on the second level of agenda building, organizational and news agendas influence each other less often. Organizational and newspaper characteristics proved useful to map the contingency of agenda-building effects. The findings suggest that organizational sources are more influential in the news discovery phase compared with the news-gathering phase, and imply that the unidirectional conceptualization of news media as a channel to vent organizational messages is too narrow.

The overload of news in today's digital information environment can lead to biased media exposure on the individual level—for example, based on the confirmation of preexisting attitudes, attractiveness of negative news, and familiarity with sources. To better understand such news patterns and to whom these selection biases apply, this study identifies different classes of (biased) news audiences and explores several antecedents. A survey in the U.S. and UK presented respondents with multiple vignettes in the form of political news headlines that were altered to reflect (1) confirmation bias, (2) negativity bias, and (3) source bias. Respondents' likelihood of selecting these biased news items was used to classify individuals into audience profiles. The results of a latent profile analysis provide three distinct and theoretically meaningful classes of news audiences that vary in terms of selection biases: avoiders, confirmers, and informers. As an important contribution, we show how these profiles are driven by the political attitudes and news preferences of audiences.

Discrimination against Roma is a reality across Europe. The extent to which stereotyped, discriminatory beliefs of this minority group are reflected or reinforced by news media has received only limited attention. This study investigates media framing of Roma and explains variation in how European news media frame Roma in diagnostic and prognostic terms. We content analysed 825 news articles from newspapers in the Netherlands, Germany, Slovakia, the Czech Republic and the United Kingdom for the period 2010–2012. Results show that attention for Roma is clustered around key-events and differs considerably between countries. Our analyses of frame variation, based on multilevel modelling, indicate a duality in the use of frames, with Roma being both portrayed as victims and perpetrators. Variation in these portrayals could be ascribed mainly to sources and newspaper types. This study contributes to our understanding of the factors that account for problem-emphasizing portrayals of Roma in European countries.

This study moves beyond previous research by demonstrating how prior exposure to stereotypical content can reinforce the selection of comparable biased news content and by clarifying its intergroup and interpersonal consequences. With two experiments ( N = 236, N = 270), we show that media effects and selectivity of biased media content about Arabic migrant workers are connected by automatic (i.e., implicit) stereotypes. The findings reveal that exposure to moderate doses of stereotypic news primes affects the selection of biased news via implicit stereotypes and subsequently shifts intergroup and interpersonal outcomes in the direction of the activated biased beliefs. These effects did not surface for high doses of stereotypic news primes, suggesting that individuals resist and inhibit activation processes when exposure is perceived to be too extreme. As subtle forms of bias are omnipresent in news environments and implicit stereotypes operate partly under the radar of conscious awareness, they may affect selection without individuals being aware of it. The findings imply that audiences' biased selectivity should not be seen in isolation from prior media exposure.

ABSTRACTOlder employees face a severe employability problem, partly because of dominant stereotypes about them. This study investigates stereotypes of older employees in corporate and news media. Drawing on the Stereotype Content Model, we content analysed newspaper coverage and corporate media of 50 large-scale Dutch organisations, published between 2006 and 2013. The data revealed that stereotypical portrayals of older employees are more common in news media than in corporate media and mixed in terms of valence. Specifically, older employees were positively portrayed with regard to warmth stereotypes, such as trustworthiness, but negatively with regard to competence stereotypes, such as technological competence and adaptability. Additionally, stereotypical portrayals that do not clearly belong to warmth or competence dimensions are found, such as the mentoring role stereotype and the costly stereotype. Because competence stereotypes weigh more heavily in employers' productivity perceptions, these media portrayals might contribute to the employability problem of older employees. We suggest that older employees could benefit from a more realistic media debate about their skills and capacities.

This study investigates users' artificial intelligence (AI)-related competencies (i.e., AI knowledge, skills, and attitudes) and identifies the vulnerable user groups in the AI-shaped online news and entertainment environment. We surveyed 1088 Dutch citizens over the age of 16 years and identified five user groups through the latent class analysis: the average users, the expert advocates, the expert skeptics, the unskilled skeptics, and the neutral unskilled. The most vulnerable groups with the lowest levels of AI knowledge and AI skills (i.e., unskilled skeptics and neutral unskilled) were mostly older, with lower levels of education and privacy protection skills, than the average users. Overall, the results of this study resonate with the existing findings on the digital divide and provide evidence for an emerging AI divide among users. Finally, the societal implication of this study is discussed, such as the need for education programs and applications of the explainable AI.

Abstract
The current study explores how the cultural distance of ethnic outgroups relative to the ethnic ingroup is related to stereotypical news representations. It does so by drawing on a sample of more than three million Dutch newspaper articles and uses advanced methods of automated content analysis, namely word embeddings. The results show that distant ethnic outgroup members (i. e., Moroccans) are associated with negative characteristics and issues, while this is not the case for close ethnic outgroup members (i. e., Belgians). The current study demonstrates the usefulness of word embeddings as a tool to study subtle aspects of ethnic bias in mass-mediated content.

Media and communication have become ubiquitous in today's societies and affect all aspects of life. On an individual level, they impact how we learn about the world, how we entertain ourselves, and how we interact with others. On an organisational level, the interactions between media and organisations, such as political parties, NGOs, businesses and brands, shape organisations' reputation, legitimacy, trust and (financial) performance, as well as individuals' consumer, political, social and health behaviours. At the societal level, media and communication are crucial for shaping public opinion on current issues such as climate change, sustainability, diversity, and well-being. Media challenges are widespread and include mis- and disinformation, the negative impact of algorithms on our information diets, challenges to our privacy, cyberbullying, media addiction, and unwanted persuasion, among many others. All this makes the study of media and communication crucial. This book provides a broad overview of the ways in which people create, use, and experience their media environment, and the role of media and communication for individuals, organisations, and society. The chapters in the book were written by researchers from the Amsterdam School of Communication Research (ASCoR) on the occasion of its 25th anniversary. ASCoR is today the largest research institute of its kind in Europe and has developed over the past 25 years into one of the best communications research institutes in the world