The ‘bad women drivers’ myth: the overrepresentation of female drivers and gender bias in China’s media

ABSTRACT

The body of literature on underrepresentation and gender inequality is vast. However, despite its potential to perpetuate gender stereotypes, the overrepresentation of women in media has received inadequate attention. This study explores how traditional news media and social media overrepresent females as drivers when discussing traffic accidents, and whether social media could be the ‘new equalizer’ for gender. Focusing on China, we collected 97,120 posts from Weibo, China’s largest microblogging site, and 11,290 newspaper articles dated between January 2010 and November 2018. We analyzed the data through a mixed-methods design and found that female drivers are overrepresented in discussions of traffic accidents, in both newspapers and on Weibo. While the gender bias against female drivers is more prevalent on Weibo than in newspapers, Weibo has provided a platform for gender-aware discussion. Our study closes by offering suggestions for cross-platform and cross-cultural comparisons of gender representation in the digital age.

KEYWORDS:

• Big data
• social media
• gender
• media studies
• China

Acknowledgements

We thank Dr. Kate Averett, Dr. Glenn Deane, Dr. Brandon Gorman, Dr. Ronald N. Jacobs, fellows at the China Study Group in the Sociology Department at the University at Albany, and two anonymous reviewers for their comments. The research was supported by the Benevolent Association Research and Creative Activity Grant, and the Karen R. Hitchcock New Frontiers Fund Award from the University at Albany, State University of New York.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Muyang Li is a Ph.D. candidate of sociology at the University at Albany – State University of New York. Her research interests include cultural sociology, computational social science, civil society and democracy, and new media [twitter: twitter.com/muyangli_soc, email: [email protected]].

Zhifan Luo is a Ph.D. candidate of sociology at the University at Albany – State University of New York. Her research interests include political sociology, computational social science, political discourse, social media, and misinformation campaign. Her works have been published in the Journal of World-Systems Research [twitter: twitter.com/zhifan_luo].

ORCID

Muyang Li http://orcid.org/0000-0003-2522-4601

Notes

1 Perceived as control-freaks.

2 Perceived as ignorant of basic soccer rules and desperate for a male partner’s ‘Soccer 101’ lecture.

3 The five top-weighted documents on the sexism topic are presented in Table 1 in the Supplementary Materials.

4 We were unable to fact check this accident, though we doubt the likelihood that a demand made ‘in a coquettish voice’ could have been heard by others on the highway.

5 The result of negative binomial regression model is presented in Table 2 in the Supplementary Materials.

6 The distribution of reposted content was similar for male and female drivers, as assessed by visual inspection. The five hundred most reposted posts from each gender-annotated group and the number of reposts they received is presented in Figure 1 in the Supplementary Materials.

7 Didi is a Chinese ride-sharing app similar to Uber. This post refers to a wave of news stories in which male Didi drivers had injured, raped, and in some cases even murdered, female passengers.

8 In the original post, the word ‘privilege’ appears in English.