“Even When Success Seems Impossible, I Keep Streaming”: How Do Chinese Elderly Streamers Interact with Platform Algorithmic (In)visibility

Recent research within the HCI community has illuminated the challenges faced by marginalized groups on algorithm-driven livestreaming platforms. However, there is a notable gap in understanding how elderly livestreamers interact with the platform content moderation and algorithmic (in)visibility. This study investigates the perceptions of the algorithm-moderated (in)visibility and the coping strategies of 16 elderly streamers on Douyin. We find that, contrary to stereotypes of elderly users as digitally uninformed, these streamers actively engage with the platform to facilitate their understanding about platform algorithm. This engagement involves official guidance, peer learning, and personal experimentation. The streamers adopt various strategies to align with the perceived algorithmic preferences. Despite their rich knowledge about the platform's visibility moderation, many elderly streamers face significant challenges, such as physical and psychological strain and low viewer traffic. We conclude with design implications for livestreaming platforms to foster fairness and promote engagement among elderly streamers.

Authors

Institutions

Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713763
Citations
2
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
4.15

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

“Even When Success Seems Impossible, I Keep Streaming”: How Do Chinese Elderly Streamers Interact with Platform Algorithmic (In)visibility

Pan Hui, Muzhi Zhou, Xian Xu, Zheng Wei et al.
2 citations
Sharing Economy and Platforms
4.15
article

“Even When Success Seems Impossible, I Keep Streaming”: How Do Chinese Elderly Streamers Interact with Platform Algorithmic (In)visibility

Pan Hui, Muzhi Zhou, Xian Xu, Zheng Wei, Jia Xin Liao, Changyang He, Zeyu Yang
article en
2 citations

Abstract

Recent research within the HCI community has illuminated the challenges faced by marginalized groups on algorithm-driven livestreaming platforms. However, there is a notable gap in understanding how elderly livestreamers interact with the platform content moderation and algorithmic (in)visibility. This study investigates the perceptions of the algorithm-moderated (in)visibility and the coping strategies of 16 elderly streamers on Douyin. We find that, contrary to stereotypes of elderly users as digitally uninformed, these streamers actively engage with the platform to facilitate their understanding about platform algorithm. This engagement involves official guidance, peer learning, and personal experimentation. The streamers adopt various strategies to align with the perceived algorithmic preferences. Despite their rich knowledge about the platform's visibility moderation, many elderly streamers face significant challenges, such as physical and psychological strain and low viewer traffic. We conclude with design implications for livestreaming platforms to foster fairness and promote engagement among elderly streamers.

Hong Kong University of Science and Technology (HK), Max Planck Institute for Security and Privacy (DE), University of Hong Kong (HK)
Guangdong Office of Philosophy and Social Science
Openalex Percentile: Top 7%
Sharing Economy and Platforms
4.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

“Even When Success Seems Impossible, I Keep Streaming”: How Do Chinese Elderly Streamers Interact with Platform Algorithmic (In)visibility — Pan Hui, Muzhi Zhou, et al. · (2025) | TGRS Research Map | TGRS