Dynamics in Two-Sided Attention Markets: Objective, Optimization, and Control
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916929944420352 |
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| author | Zhu, Haiqing Cheung, Yun Kuen Xie, Lexing |
| author_facet | Zhu, Haiqing Cheung, Yun Kuen Xie, Lexing |
| contents | With most content distributed online and mediated by platforms, there is a pressing need to understand the ecosystem of content creation and consumption. A considerable body of recent work shed light on the one-sided market on creator-platform or user-platform interactions, showing key properties of static (Nash) equilibria and online learning. In this work, we examine the {\it two-sided} market including the platform and both users and creators. We design a potential function for the coupled interactions among users, platform and creators. We show that such coupling of creators' best-response dynamics with users' multilogit choices is equivalent to mirror descent on this potential function. Furthermore, a range of platform ranking strategies correspond to a family of potential functions, and the dynamics of two-sided interactions still correspond to mirror descent. We also provide new local convergence result for mirror descent in non-convex functions, which could be of independent interest. Our results provide a theoretical foundation for explaining the diverse outcomes observed in attention markets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01970 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dynamics in Two-Sided Attention Markets: Objective, Optimization, and Control Zhu, Haiqing Cheung, Yun Kuen Xie, Lexing Social and Information Networks Computer Science and Game Theory With most content distributed online and mediated by platforms, there is a pressing need to understand the ecosystem of content creation and consumption. A considerable body of recent work shed light on the one-sided market on creator-platform or user-platform interactions, showing key properties of static (Nash) equilibria and online learning. In this work, we examine the {\it two-sided} market including the platform and both users and creators. We design a potential function for the coupled interactions among users, platform and creators. We show that such coupling of creators' best-response dynamics with users' multilogit choices is equivalent to mirror descent on this potential function. Furthermore, a range of platform ranking strategies correspond to a family of potential functions, and the dynamics of two-sided interactions still correspond to mirror descent. We also provide new local convergence result for mirror descent in non-convex functions, which could be of independent interest. Our results provide a theoretical foundation for explaining the diverse outcomes observed in attention markets. |
| title | Dynamics in Two-Sided Attention Markets: Objective, Optimization, and Control |
| topic | Social and Information Networks Computer Science and Game Theory |
| url | https://arxiv.org/abs/2509.01970 |