Playing to Save Sisters: How Female Gaming Communities Foster Social Support within Different Cultural Contexts

ABSTRACT

Gender bias frequently exists in gaming culture, and online communities have formed separatist safe spaces to provide female players with social support. This study is based on text mining of female player communities on two platforms, Reddit and Douban. Text analysis methods containing Structural Topic Model and Linguistic Inquiry and Word Count were employed to explore how social support is presented and how topics and language features – including community identity, affection, and gender-related expressions – influence the social support that a post receives. Similarities and differences in these relationships are compared between two communities, representing Western individualist and Chinese collectivist cultures.

Acknowledgments

We would like to express our great thanks to Prof. Lan Peng for her generous help on this project. We also thank three anonymous reviewers for their insightful suggestions on this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/08838151.2023.2254432

Notes

¹ We understand that the term “female” refers to biological sex while “woman” is gender identity (American Psychological Association, 2009). In the present study, female gamers are people who self-identify as a female game player (Yao et al., 2022).

Additional information

Notes on contributors

Zizhong Zhang

Zizhong Zhang (M.A., Tsinghua University) is a Ph.D. candidate in the School of Journalism and Communication at Tsinghua University. His research interests include game studies, computational communication, and media psychology.

Haixin Mu

Haixin Mu (M.A., Tsinghua University) is a Ph.D. student in the School of Journalism and Communication at The Chinese University of Hong Kong. Her research interests include computational social science, political communication, and feminist studies.

Sida Huang

Sida Huang (B.A., The Chinese University of Hong Kong) is a Master’s student in Data Science Institute at Columbia University. His research interests include big data mining and analysis.