ArticlePublisher preview available

Mentions of prejudice in news media – an international comparison

Authors:
To read the full-text of this research, you can request a copy directly from the author.

Abstract and Figures

Previous research has identified a post-2010 sharp increase of terms used to denounce prejudice (i.e. racism, sexism, homophobia, Islamophobia, anti-Semitism, etc.) in U.S. and U.K. news media content. Here, we extend previous analysis to an international sample of news media organizations. Thus, we quantify the prevalence of prejudice-denouncing terms and social justice associated terminology (diversity, inclusion, equality, etc.) in over 98 million news and opinion articles across 124 popular news media outlets from 36 countries representing 6 different world regions: English-speaking West, continental Europe, Latin America, sub-Saharan Africa, Persian Gulf region and Asia. We find that the post-2010 increasing prominence in news media of the studied terminology is not circumscribed to the U.S. and the U.K. but rather appears to be a mostly global phenomenon starting in the first half of the 2010s decade in pioneering countries yet largely prevalent around the globe post-2015. However, different world regions’ news media emphasize distinct types of prejudice with varying degrees of intensity. We find no evidence of U.S. news media having been first in the world in increasing the frequency of prejudice coverage in their content. The large degree of temporal synchronicity with which the studied set of terms increased in news media across a vast majority of countries raises important questions about the root causes driving this phenomenon.
This content is subject to copyright. Terms and conditions apply.
RESEARCH ARTICLE
Journal of Computational Social Science (2024) 7:1965–1983
https://doi.org/10.1007/s42001-024-00295-2
Abstract
Previous research has identied a post-2010 sharp increase of terms used to de-
nounce prejudice (i.e. racism, sexism, homophobia, Islamophobia, anti-Semitism,
etc.) in U.S. and U.K. news media content. Here, we extend previous analysis to
an international sample of news media organizations. Thus, we quantify the preva-
lence of prejudice-denouncing terms and social justice associated terminology (di-
versity, inclusion, equality, etc.) in over 98 million news and opinion articles across
124 popular news media outlets from 36 countries representing 6 dierent world
regions: English-speaking West, continental Europe, Latin America, sub-Saharan
Africa, Persian Gulf region and Asia. We nd that the post-2010 increasing promi-
nence in news media of the studied terminology is not circumscribed to the U.S.
and the U.K. but rather appears to be a mostly global phenomenon starting in the
rst half of the 2010s decade in pioneering countries yet largely prevalent around
the globe post-2015. However, dierent world regions’ news media emphasize dis-
tinct types of prejudice with varying degrees of intensity. We nd no evidence
of U.S. news media having been rst in the world in increasing the frequency of
prejudice coverage in their content. The large degree of temporal synchronicity with
which the studied set of terms increased in news media across a vast majority of
countries raises important questions about the root causes driving this phenomenon.
Keywords News media · Agenda setting · Prejudice · The Great Awokening ·
Wokeness · Social justice · Racism · Sexism · Homophobia · DEI
Received: 3 January 2024 / Accepted: 15 May 2024 / Published online: 11 June 2024
© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024
Mentions of prejudice in news media – an international
comparison
DavidRozado1
David Rozado
david.rozado@op.ac.nz
1 Otago Polytechnic, Forth Street, Dunedin 9016, New Zealand
1 3
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... This environment fosters ethical awareness and cultural openness, yet tends to marginalize material concerns. As recent research indicates, British and American journalism has experienced a substantial increase in references to various forms of prejudice related to race, gender, sexuality, and religion since 2010 (Rozado, 2024). A parallel trend can be observed in academic writing, where terminology associated with social justice and the denunciation of bias has proliferated markedly in the same period. ...
Article
In the widely acclaimed BrexLit Middle England (2018), Jonathan Coe foregrounds the role of media in both unifying and dividing a nation on the brink of political rupture. While many existing studies of BrexLit have focused on race, class, and generational divides, this paper highlights media as a critical but under-examined force in shaping political subjectivities and group dynamics among British people. Through a close analysis of three social groups in the novel, represented respectively by Sophie Potter, Ian Coleman, and Colin Trotter, the paper presents how divergent media preferences position them within distinct media ecologies by shaping their cognitive framework and affective dispositions. It also shows how such differences were further exploited by the campaign media during the referendum, which deepened group divisions and intensified ideological contestations. Therefore, Middle England reveals how contemporary media landscapes contribute to the divisions of social groups, inviting BrexLit criticism to move beyond cataloguing divisions toward analyzing the mediatized processes by the media that make the Brexit divisions become inevitable.
Article
Full-text available
With the development of artificial intelligence (AI), new horizons are opening in the creation and adaptation of visual content, making it possible not only to automate certain processes but also to create interactive and dynamic visualizations that can significantly enhance interaction with information. The use of AI in news visualization allows journalists and media organizations not only to improve the quality and accessibility of information but also to offer the audience a unique and engaging experience. The aim of the research is to systematize the various forms of visualization used in contemporary journalism and the possibility of integrating AI into these processes. To achieve the set goals, a review of current scientific works and publications on the topic was conducted, as well as a review of examples of modern forms of visualization that were created with the help of AI in various journalism genres. The methodology of this study focuses on four key approaches: general scientific methods, analytical review of scientific literature on the topic, experimental study using ChatGPT (4GPT) chatbot, and classification of modern forms of visualization. The scientific and practical significance of the work is determined by the in-depth study of the classification of visual forms used in media communications, which contributes not only to expanding theoretical knowledge in the field of media visualization but also to developing content creation strategies integrating the most effective and innovative forms of visualization. As a result of the research, an attempt was made to classify modern forms of visualization, which suggests an advantage in understanding and using visual data in various fields. The conclusion of the article emphasizes that the introduction of artificial intelligence and neural networks opens new horizons for the development of modern forms of visualization, playing a key role in adapting journalistic content to the needs of the digital era. The use of these technologies allows not only to automate the visualization creation process, making it more efficient and scalable, but also offers possibilities for creating more complex, interactive, and personalized visual materials. This improves interaction with the audience, makes information more accessible and understandable, increasing the overall effectiveness of journalistic materials.
Article
Full-text available
This work describes a chronological (2000–2019) analysis of sentiment and emotion in 23 million headlines from 47 news media outlets popular in the United States. We use Transformer language models fine-tuned for detection of sentiment (positive, negative) and Ekman’s six basic emotions (anger, disgust, fear, joy, sadness, surprise) plus neutral to automatically label the headlines. Results show an increase of sentiment negativity in headlines across written news media since the year 2000. Headlines from right-leaning news media have been, on average, consistently more negative than headlines from left-leaning outlets over the entire studied time period. The chronological analysis of headlines emotionality shows a growing proportion of headlines denoting anger, fear, disgust and sadness and a decrease in the prevalence of emotionally neutral headlines across the studied outlets over the 2000–2019 interval. The prevalence of headlines denoting anger appears to be higher, on average, in right-leaning news outlets than in left-leaning news media.
Technical Report
Full-text available
• Recent years have seen considerable debate about the rise of political polarisation in British society. Specifically, over the last decade, various studies have suggested that the UK is now rapidly following the United States into a more polarised politics in which intensifying ‘culture wars’ over issues such as racism, identity, diversity, history, the legacy of history, and ‘social justice’ or so-called ‘woke’ politics are becoming far more prominent. • While this debate typically focuses on the role of party politics, much less attention has focused on the relationship between news media and rising polarisation. Building on recent pioneering research which has tracked a sharp increase in the overall prominence of prejudice and social justice rhetoric in US and Spanish media, our purpose in this report is to explore whether similar trends are now also visible in the UK. • We use computational content analysis to explore the chronological prevalence in UK news media of words which denote prejudice (i.e., sexism, racism, homophobia, etc.) and ‘social justice’ or ‘woke’ rhetoric (i.e., white privilege, whiteness, cultural appropriation, diversity, etc.). Our main interest in doing so is to explore how the media debate has changed over time. • Thus, we present analyses of UK media usage of these terms between the years 2000 and 2020 in 16 million news and opinion articles, published in a nationally representative sample of ten popular British media outlets: The Guardian, The Independent, The Daily Mirror, BBC, The Times, Financial Times, Metro, The Telegraph, Daily Mail and The Sun. To our knowledge, this is the most comprehensive analysis of UK media coverage of these issues to date. • Consistent with recent studies in the U.S. and Spain, we find that references to prejudice and social justice rhetoric have increased sharply in UK media in recent years. Between 2010 and 2020, terms such as racism and white supremacy in popular UK media outlets increased on average by 769% and 2,827% respectively, while terms such as sexism, patriarchy and misogyny increased by 169%, 336% and 237% each. Additional terms such as transphobia, islamophobia and anti-semitism increased by 2,578%, 289% and 469% respectively. Similarly, terms associated with social justice discourse have also markedly increased over the same temporal period: diversity (199%), activism (146%), hate speech (880%), inequality (218%), gender-neutral (1,019%) or slavery (413%). • These sharp increases are pervasive across media, regardless of their ideological leanings. But overall prevalence tends to be larger in left-leaning outlets. Mentions of prejudice have also become far more prominent in the BBC, the UK’s leading public service outlet. From 2010 to 2020, mentions in BBC content of terms suggestive of racism have increased by over 802% while mentions of terms suggestive of sexism have increased by 610%. Mentions of homophobia and transphobia increased by 134% and 3,341% respectively. Terms signifying islamophobia and anti-Semitism increased by 585% and 2,431%. • By tracking the temporal prevalence of terms denoting prejudice and social justice in UK news media, we throw light on how the UK media debate is evolving and raise important questions about whether media institutions have got the balance right in how we talk about these issues. In the final section, we consider possible explanations for the sharp increase in the prominence of prejudice and social justice rhetoric in UK news media, including the shifting profile of the UK media class which has increasingly become far more elite.
Article
Full-text available
The term political extremism is commonly used to refer to political attitudes considered to be outside the ideological mainstream. This study leverages computational content analysis of big data to longitudinally examine (1970–2019) the prevalence of terms denoting far-right and far-left political extremism in more than 30 million written news and opinion articles from 54 news media outlets popular in the United States and the United Kingdom. We find that the usage of terms denoting right and left political extremism has been increasing across news media outlets in both countries. This trend is particularly stark for far-right-denoting terms, which have been growing in prevalence since at least 2008. Most U.S. and U.K. news media outlets tend to use far-right-denoting terms substantially more often than they use far-left-denoting terms. The rising prevalence in news media of terms denoting political extremism is strongly correlated with similar growing usage of terms denoting prejudice and social justice discourse.
Article
Full-text available
Previous scholarly literature has documented a pronounced increase in the prevalence of prejudice-denoting terms in American news media content. Some have referred to this shift in journalistic discourse and related public opinion trends signaling increasing perceptions of prejudice severity in U.S. society as The Great Awokening. This work analyzes whether the increasing prevalence of prejudice themes in American news media outlets has been replicated in the news media ecosystem of a Spanish-speaking country. Thus, we computationally analyzed the prevalence of words denoting prejudice in five million news and opinion articles written between 1976 and 2019 and published in three of the most widely read newspapers in Spain: El País, El Mundo and ABC. We report that within the studied time period, the frequency of terms that denote specific prejudice types related to gender, ethnicity, sexuality and religious orientation has also substantially increased across the analyzed Spanish news media outlets. There are, however, some notable distinctions in the long-term usage dynamics of prejudice-denoting terms between the leading Spanish newspaper of record, El País, and its U.S. counterpart, The New York Times.
Article
Full-text available
We gathered survey data on journalists' political views in 17 Western countries. We then matched these data to outcomes from national elections, and constructed metrics of journalists' relative preference for different political parties. Compared to the general population of voters, journalists prefer parties that have more left-wing positions overall (r's-.47 to-.53, depending on the metric used), and that are associated with certain ideologies, namely environmentalism, feminism, social liberalism, socialism, and support for the European Union. We used Bayesian model averaging to assess the validity of the predictors in multivariate models. We found that, of the ideology tags in our dataset, 'conservative' (negative), 'nationalist' (negative) and 'green' (positive) were the most consistent predictors with nontrivial effect sizes. We also computed estimates of the skew of journalists' political views in different countries. Overall, our results indicate that the Western media has a left-liberal skew.
Article
Full-text available
This work analyzes the prevalence of words denoting prejudice in 27 million news and opinion articles written between 1970 and 2019 and published in 47 of the most popular news media outlets in the United States. Our results show that the frequency of words that denote specific prejudice types related to ethnicity, gender, sexual, and religious orientation has markedly increased within the 2010–2019 decade across most news media outlets. This phenomenon starts prior to, but appears to accelerate after, 2015. The frequency of prejudice-denoting words in news articles is not synchronous across all outlets, with the yearly prevalence of such words in some influential news media outlets being predictive of those words’ usage frequency in other outlets the following year. Increasing prevalence of prejudice-denoting words in news media discourse is often substantially correlated with U.S. public opinion survey data on growing perceptions of minorities’ mistreatment. Granger tests suggest that the prevalence of prejudice-denoting terms in news outlets might be predictive of shifts in public perceptions of prejudice severity in society for some, but not all, types of prejudice.
Article
Full-text available
This work describes an analysis of political associations in 27 million diachronic (1975–2019) news and opinion articles from 47 news media outlets popular in the United States. We use embedding models trained on individual outlets content to quantify outlet-specific latent associations between positive/negative sentiment words and terms loaded with political connotations such as those describing political orientation, party affiliation, names of influential politicians, and ideologically aligned public figures. We observe that both left- and right-leaning news media tend to associate positive sentiment words with terms used to refer to members of their own political in-group and negative sentiment words with terms used to denote members of their ideological outgroup. Outlets rated as centrist by humans display political associations that are often milder but similar in orientation to those of left-leaning news organizations. A weighted average of political associations by outlets’ readership volume hints that political associations embedded in left of center news outlets might have larger societal reach. A chronological analysis of political associations through time suggests that political sentiment polarization is increasing in both left- and right-leaning news media contents. Our approach for measuring sentiment associations of words denoting political orientation in outlet-specific embedding models correlates substantially with external human ratings of outlet ideological bias (r > 0.7). Yet, specific sentiment associations are sometimes multifaceted and challenging to interpret. Overall, our work signals the potential of machine learning models derived from news media language usage to quantify the ideological bias embedded in news outlet content.
Article
Full-text available
Significance Almost four billion people around the world now use social media platforms such as Facebook and Twitter, and social media is one of the primary ways people access news or receive communications from politicians. However, social media may be creating perverse incentives for divisive content because this content is particularly likely to go “viral.” We report evidence that posts about political opponents are substantially more likely to be shared on social media and that this out-group effect is much stronger than other established predictors of social media sharing, such as emotional language. These findings contribute to scholarly debates about the role of social media in political polarization and can inform solutions for creating healthier social media environments.
Article
Despite a marked decline in prejudicial attitudes among the public at large, a survey of 175 million scholarly articles published over the last five decades has found a sharp spike in words denoting prejudice and social justice themes beginning in 2010 and lasting at least through the first few months of 2020, a pattern observed within news media content as well.
Article
Racial attitudes are multidimensional, and the corresponding picture we get from survey data on racial attitudes is complex. Tracing the results of major national surveys that provide trends over at least 10 years, and with at least three time points (primarily the General Social Survey and the National Election Studies), this article reveals that complexity. Some survey questions show dramatic changes in support of racial equality, while others reveal stagnation or even increasing negativity or disinterest. The article also describes the differences between whites and blacks in patterns and trends. Although compared to some issues, the survey record on racial attitudes is robust and lengthy, we draw attention to important ways in which it is uneven. We conclude by highlighting areas for future research that focus on improved survey measures that will capture more fully the complexity of contemporary public opinion on racial matters.