Residential College | false |
Status | 已發表Published |
Underrepresentation and Biased Representation of Frontline Women Health Workers in Chinese Social Media | |
李小勤, Li, Xiaoqin1; Wang, Yunwen2; Xiao, Qian1 | |
2022-05 | |
Conference Name | the hybrid 72nd Annual ICA Conference |
Conference Date | May 26-30, 2022 |
Conference Place | Paris-Hybrid |
Country | France-Hybrid |
Author of Source | Xiaoqin Li ; Yunwen Wang ; Qian Xiao |
Abstract | Women constitute the major force in the frontline health sector under the unprecedented pressure of COVID-19. Nevertheless, we found that women health workers were still unrepresented and represented with biased on social media. This study used Latent Dirichlet Allocation (LDA) topic modeling to analyze posts (N = 199,110) containing the keyword “援鄂医疗队” (i.e., “aiding-Hubei medical team”) published in the first stage of COVID-19 (January 22, 2020 to June 30, 2020) on a Chinese social media, Weibo. Results revealed that health workers were discussed in relation to serving the “nation,” saving the “patients,” and fulfilling family roles. Among the 13 topics in this online discourse, topics discussing health workers in a non-gendered lens tended to emphasize their professional role. When the female identity of health workers was explicit, depictions tended to emphasize their family roles. Meanwhile, the wave-riding and hashtag-jumping/hijacking of corporates and male celebrities – in celebration of their charitable work toward the COVID-19 medical teams – also deprived women health workers of their voices and visibility. Theoretical and practical implications of women health workers’ social media underrepresentation and misrepresentation are discussed.
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Keyword | Health Worker Gender Stereotype Media Representation Familism Hashtag-jumping Computational Text Analysis |
Language | 英語English |
Document Type | Conference paper |
Collection | Faculty of Social Sciences DEPARTMENT OF COMMUNICATION |
Affiliation | 1.Department of Communication, FSS, University of Macau 2.Annenberg School for Communication and Journalism, University of Southern California |
First Author Affilication | Faculty of Social Sciences |
Recommended Citation GB/T 7714 | 李小勤, Li, Xiaoqin,Wang, Yunwen,Xiao, Qian. Underrepresentation and Biased Representation of Frontline Women Health Workers in Chinese Social Media[C]. Xiaoqin Li, Yunwen Wang, Qian Xiao, 2022. |
APA | 李小勤, Li, Xiaoqin., Wang, Yunwen., & Xiao, Qian (2022). Underrepresentation and Biased Representation of Frontline Women Health Workers in Chinese Social Media. . |
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