Behind the Same Mask: Understanding the Practice of Spontaneous Collective Anonymity on Chinese Social Platforms

Anonymity plays a crucial role in social interactions online. Recently, a new phenomenon has emerged on Chinese social platforms where users collectively adopt a uniform avatar and nickname ''momo'', thereby achieving anonymity. However, understanding such spontaneous collective anonymity within Chinese cultural and contextual factors remains limited since much of the anonymity research focuses on Western users. Yet, it is unclear how users perceive the usage of ''momo'', their motivations, and how using this collective anonymity impacts their social interaction. To answer these questions, we conducted interviews with 20 ''momo'' users. We found that the shared identity ''momo'' provides an additional layer of anonymity on identity-constrained Chinese social platforms. Users adopted ''momo'' to engage in more inclusive discussions and to balance anonymity and self-presentation. Moreover, this collective anonymity fosters connections and forms a meaningful group identity in a loosely organized community. We also identified the benefits and risks associated with this unique collective anonymity. This work makes significant contributions to CSCW and HCI research by (1) extending the knowledge of anonymity practices and privacy concerns within non-Western and mainly Chinese contexts. (2) advancing the work on anonymity models by revealing the dual role of the Momo identity in facilitating collective anonymity and community bonds. (3) providing design implications to support future social technologies in identity design and anonymous communities.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-05-02
DOI
https://doi.org/10.1145/3710933
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
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article

Behind the Same Mask: Understanding the Practice of Spontaneous Collective Anonymity on Chinese Social Platforms

Yaxing Yao, Zhicong Lu, Weijun Li, Shi Chen et al.
Proceedings of the ACM on Human-Computer Interaction
Privacy, Security, and Data Protection
article

Behind the Same Mask: Understanding the Practice of Spontaneous Collective Anonymity on Chinese Social Platforms

Yaxing Yao, Zhicong Lu, Weijun Li, Shi Chen, Chao Zhang, Suqi Lou
article en

Abstract

Anonymity plays a crucial role in social interactions online. Recently, a new phenomenon has emerged on Chinese social platforms where users collectively adopt a uniform avatar and nickname ''momo'', thereby achieving anonymity. However, understanding such spontaneous collective anonymity within Chinese cultural and contextual factors remains limited since much of the anonymity research focuses on Western users. Yet, it is unclear how users perceive the usage of ''momo'', their motivations, and how using this collective anonymity impacts their social interaction. To answer these questions, we conducted interviews with 20 ''momo'' users. We found that the shared identity ''momo'' provides an additional layer of anonymity on identity-constrained Chinese social platforms. Users adopted ''momo'' to engage in more inclusive discussions and to balance anonymity and self-presentation. Moreover, this collective anonymity fosters connections and forms a meaningful group identity in a loosely organized community. We also identified the benefits and risks associated with this unique collective anonymity. This work makes significant contributions to CSCW and HCI research by (1) extending the knowledge of anonymity practices and privacy concerns within non-Western and mainly Chinese contexts. (2) advancing the work on anonymity models by revealing the dual role of the Momo identity in facilitating collective anonymity and community bonds. (3) providing design implications to support future social technologies in identity design and anonymous communities.

Proceedings of the ACM on Human-Computer InteractionVol. 9(2)
George Mason University (US), University of California, Irvine (US), Cornell University (US), Zhejiang University (CN), Virginia Tech (US)
Reduced inequalities
Openalex Percentile: Top 85%
Privacy, Security, and Data Protection
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