Mentions of Prejudice in News Media -- An International Comparison
Tags: machinelearning, ai, beginners, datascience
Published: 2024-05-06 11:39:06

*This is a Plain English Papers summary of a research paper called [Mentions of Prejudice in News Media -- An International Comparison](https://aimodels.fyi/papers/arxiv/mentions-prejudice-news-media-international-comparison). If you like these kinds of analysis, you should subscribe to the [AImodels.fyi newsletter](https://aimodels.substack.com) or follow me on [Twitter](https://twitter.com/mikeyoung44).*

## Overview

- This research examines the increasing prevalence of terms used to denounce prejudice (e.g., racism, sexism, homophobia) and social justice-related terminology (e.g., diversity, inclusion, equality) in news media content across 36 countries and 6 world regions.
- The study quantifies the usage of these terms in over 98 million news and opinion articles from 124 popular news outlets.
- The findings suggest that the post-2010 rise in prejudice-denouncing and social justice terminology is not limited to the U.S. and U.K. but is a largely global phenomenon, with varying degrees of emphasis across different regions.

## Plain English Explanation

The researchers investigated the use of certain words and phrases in news articles from around the world. These words and phrases are often used to call out or condemn prejudice, such as racism, sexism, and discrimination against specific groups. The researchers also looked at words and phrases related to social justice, like "diversity," "inclusion," and "equality."

The researchers found that the use of these types of terms has increased significantly in news media since around 2010, and this trend is not just limited to the United States and United Kingdom. [It appears to be a global phenomenon](https://aimodels.fyi/papers/arxiv/global-news-synchrony-diversity-during-start-covid), with news outlets in different regions of the world emphasizing different types of prejudice to varying degrees.

Interestingly, the researchers did not find evidence that U.S. news media were the first in the world to increase their coverage of prejudice-related issues. The widespread and synchronous increase in this type of language across many countries raises important questions about what might be driving this shift in news reporting. [It could be related to broader societal changes and debates around issues of discrimination and social justice](https://aimodels.fyi/papers/arxiv/us-election-hardens-hate-universe).

## Technical Explanation

The researchers conducted a quantitative analysis of the prevalence of prejudice-denouncing terms (e.g., racism, sexism, homophobia) and social justice-associated terminology (e.g., diversity, inclusion, equality) in news and opinion articles from 124 popular media outlets across 36 countries and 6 world regions.

They compiled a corpus of over 98 million articles published between 2000 and 2020 and used computational text analysis techniques to measure the frequency of the studied terms. The analysis revealed a sharp increase in the usage of these terms starting in the early 2010s, which was not limited to the U.S. and U.K. but rather appeared to be a global phenomenon.

The researchers found that different regions emphasized distinct types of prejudice with varying degrees of intensity. For example, news media in the Persian Gulf region focused more on anti-Semitism, while outlets in sub-Saharan Africa placed greater emphasis on racism. Contrary to popular perception, the researchers did not find evidence that U.S. news media were the first in the world to increase their coverage of prejudice-related issues.

The high degree of temporal synchronicity in the increased usage of the studied terminology across a vast majority of countries raises important questions about the underlying drivers of this phenomenon. [It could be linked to broader societal shifts and debates around diversity, inclusion, and social justice](https://aimodels.fyi/papers/arxiv/exploring-boundaries-intensities-offensive-hate-speech-unveiling), which may have influenced news reporting practices globally.

## Critical Analysis

The researchers acknowledge that their study does not delve into the nuances of how the identified terminology is used in news articles, such as the context, framing, and overall sentiment. [Further research would be needed to better understand the implications of the observed trends and their connection to real-world events and societal changes](https://aimodels.fyi/papers/arxiv/computational-analysis-dehumanisation-migrants-from-syria-ukraine).

Additionally, the analysis is limited to a specific set of terms related to prejudice and social justice, and it is possible that other relevant terminology was not captured. The researchers also note that the news media outlets included in the study may not be fully representative of the global news landscape, as they focused on popular and influential outlets.

While the findings suggest a widespread and synchronous increase in the usage of the studied terminology, it is important to consider potential confounding factors, such as changes in journalistic practices, editorial policies, and audience preferences, which could also contribute to the observed trends.

## Conclusion

This research provides valuable insights into the global evolution of news media coverage related to prejudice, discrimination, and social justice issues. The study's key finding is that the post-2010 increase in the use of prejudice-denouncing and social justice-associated terminology is not exclusive to the U.S. and U.K. but rather appears to be a largely global phenomenon, with varying degrees of emphasis across different world regions.

The synchronous nature of this trend across many countries raises intriguing questions about the underlying drivers, which could be linked to broader societal shifts and debates around diversity, inclusion, and social justice. [Further research is needed to better understand the nuances and implications of these changes in news reporting practices and their potential impact on public discourse and societal perceptions](https://aimodels.fyi/papers/arxiv/from-languages-to-geographies-towards-evaluating-cultural).

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