O'Reilly, T;
Strauss, I;
Mazzucato, M;
(2024)
Algorithmic attention rents: A theory of digital platform market power.
Data and Policy
, 6
, Article e6. 10.1017/dap.2024.1.
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Abstract
We outline a theory of algorithmic attention rents in digital aggregator platforms. We explore the way that as platforms grow, they become increasingly capable of extracting rents from a variety of actors in their ecosystems - users, suppliers, and advertisers - through their algorithmic control over user attention. We focus our analysis on advertising business models, in which attention harvested from users is monetized by reselling the attention to suppliers or other advertisers, though we believe the theory has relevance to other online business models as well. We argue that regulations should mandate the disclosure of the operating metrics that platforms use to allocate user attention and shape the free side of their marketplace, as well as details on how that attention is monetized.
| Type: | Article |
|---|---|
| Title: | Algorithmic attention rents: A theory of digital platform market power |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1017/dap.2024.1 |
| Publisher version: | http://dx.doi.org/10.1017/dap.2024.1 |
| Language: | English |
| Additional information: | Creative Common License - CCCreative Common License - BY This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. Copyright © The Author(s), 2024. Published by Cambridge University Press |
| Keywords: | advertising, algorithms, business models, platforms, regulation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Inst for Innovation and Public Purpose |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10188892 |
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