| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP16624 |
| DP16624 Visual Representation and Stereotypes in News Media | |
| Elliott Ash; Ruben Durante; Mariia Grebenshchikova; Carlo Schwarz | |
| 发表日期 | 2022-05-01 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | We propose and validate a new method to measure gender and ethnic stereotypes in news reports, using computer vision tools to assess the gender, race and ethnicity of individuals depicted in article images. Applying this approach to 700,000 web articles published in the New York Times and Fox News between 2000 and 2020, we find that males and whites are overrepresented relative to their population share, while women and Hispanics are underrepresented. Relating images to text, we find that news content perpetuates common stereotypes such as associating Blacks and Hispanics with low-skill jobs, crime, and poverty, and Asians with high-skill jobs and science. Analyzing news coverage of specific jobs, we show that racial stereotypes hold even after controlling for the actual share of a group in a given occupation. Finally, we document that group representation in the news is influenced by the gender and ethnic identity of authors and editors. |
| 主题 | Political Economy ; Public Economics |
| 关键词 | Stereotypes Gender Race Media Computer vision Text analysis |
| URL | https://cepr.org/publications/dp16624-3 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/546284 |
| 推荐引用方式 GB/T 7714 | Elliott Ash,Ruben Durante,Mariia Grebenshchikova,et al. DP16624 Visual Representation and Stereotypes in News Media. 2022. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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