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Information Disclosure and Network Formation in News Subscription Services

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sword-2021-04-05T18:56:40.original.xml (130 B)
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Author(s)
Hsu, Chin-Chia
•
Ajorlou, Amir
•
Yildiz, Muhamet
•
Jadbabaie, Ali
Date Issued
January 2021
Journal
2020 59th IEEE Conference on Decision and Control
Publisher
IEEE
Citation
Hsu, Chin-Chia et al. “Information Disclosure and Network Formation in News Subscription Services.” 2020 59th IEEE Conference on Decision and Control, December 2020, Jeju, South Korea, January 2021, IEEE. © 2020 The Author(s)
Version
Original manuscript
Abstract
We study the formation of a subscription network where a continuum of strategic, Bayesian subscribers decide to subscribe to one of two sources (leaders) for news that is informative about an underlying state of the world. The leaders, aiming to maximize the welfare of all subscribers, have a motive to persuade the subscribers to take the optimal binary action against the state according to their own perspectives. With this persuasion motive, each leader decides whether to disclose the news to her own subscribers when there is news. When the subscribers receive the news, they update their beliefs; more importantly, even when no news is disclosed, the subscribers update their beliefs, speculating that there may be news that was concealed due to the leader's strategic disclosure decision. We prove that at any equilibrium, the set of news signals that are concealed by the leaders takes the form of an interval. We further show that when two leaders represent polarized and opposing perspectives, anti-homophily emerges among the subscribers whose perspectives are in the middle. For any subscriber with a perspective on the extremes, and for any leader, there exists an equilibrium at which the subscriber would follow the leader. Our results shed light on how individuals would seek information when information is private or costly to obtain, while considering the strategic disclosure by the news providers who are partisan and have a hidden motive to persuade their followers.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Economics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/130386
DOI of Published Version
https://doi.org/10.1109/CDC42340.2020.9303737
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