Persuasion, News Sharing, and Cascades on Social Networks

35 Pages Posted: 1 Oct 2021 Last revised: 6 Apr 2022

See all articles by Chin-Chia Hsu

Chin-Chia Hsu

Office of Applied Research, Microsoft

Amir Ajorlou

Massachusetts Institute of Technology - Laboratory for Information and Decision Systems

Ali Jadbabaie

Institute for Data, Systems, and Society, Massachusetts Institute of Technology

Date Written: April 5, 2022

Abstract

We develop a game-theoretic model of sharing decisions among online users of a Twitter-like social network. Each agent is endowed with a subjective prior on an unobservable real-valued state, representing their beliefs on a topic subject to a binary vote. Agents cast their binary vote matching the sign of their expected belief on the true state. Prior to the voting stage, some agents receive a piece of news which impacts their belief. Those who receive the news update their belief and make a decision as to whether to share the news with their followers so as to influence their beliefs, and in turn their votes, given a nominal cost for sharing. We characterize the underlying news spread as an endogenous Susceptible-Infected (SI) epidemic process and derive agents’ sharing decisions as well as the size of the sharing cascade at the equilibrium of the game. We show that lower credibility news can result in a larger cascade than fully credible news provided that the network connectivity surpasses a connectivity limit. We further delineate the relationship between cascade size, network connectivity, and news credibility in terms of polarization and diversity in prior beliefs: We demonstrate that increased polarization reduces the connectivity limit whereas larger in-party diversity has a non-monotone effect on the connectivity limit, which depends on both the levels of polarization and in-party diversity. Our results provide a theoretical foundation for recent empirical observations demonstrating faster and wider spread of low-credibility and false information on social networks.

Keywords: Persuasion, Strategic News Sharing, Spread of Information, Social Networks

JEL Classification: D01, D82, D83

Suggested Citation

Hsu, Chin-Chia and Ajorlou, Amir and Jadbabaie, Ali, Persuasion, News Sharing, and Cascades on Social Networks (April 5, 2022). Available at SSRN: https://ssrn.com/abstract=3934010 or http://dx.doi.org/10.2139/ssrn.3934010

Chin-Chia Hsu (Contact Author)

Office of Applied Research, Microsoft ( email )

One Microsoft Way
Redmond, WA 98052
United States

Amir Ajorlou

Massachusetts Institute of Technology - Laboratory for Information and Decision Systems ( email )

E32-D569, 32 Vassar Street,
Cambridge, MA 02139
United States
215-919-3234 (Phone)

HOME PAGE: http://www.mit.edu/~ajorlou

Ali Jadbabaie

Institute for Data, Systems, and Society, Massachusetts Institute of Technology ( email )

77 Massachusetts Ave E18-309C
E18-309C
02139, MA MA 02139
United States
6172537339 (Phone)
6172537339 (Fax)

HOME PAGE: http://web.mit.edu/www/jadbabai

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