Persuasion, News Sharing, and Cascades on Social Networks

42 Pages Posted: 1 Oct 2021 Last revised: 8 Jan 2022

See all articles by Chin-Chia Hsu

Chin-Chia Hsu

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

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: December 10, 2021

Abstract

We develop a game-theoretic model of sharing decisions among online users of a Twitter-like social network. Each agent has a subjective prior on an unobservable real-valued state. When receiving news, agents make a decision as to whether they should share the news with their followers based on how persuasive the news may be to move their followers' opinions closer to theirs while incurring a nominal cost. We characterize the dynamics of spread as an endogenous Susceptible-Infected (SI) epidemic process and derive agents' sharing decisions and the size of the cascade spread at the equilibrium of the corresponding game. We show that low credibility news can result in a larger cascade than credible news when the network is highly connected. We further show that increased polarization in prior beliefs in the population prompts more sharing of lower credibility news, resulting in larger cascade size. Finally, we fully characterize the relationship between cascade size, network connectivity, and news credibility in terms of polarization and diversity of prior beliefs. 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 (December 10, 2021). Available at SSRN: https://ssrn.com/abstract=3934010 or http://dx.doi.org/10.2139/ssrn.3934010

Chin-Chia Hsu (Contact Author)

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

77 Massachusetts Ave E17-442
Cambridge, MA 02139
United States
6179490669 (Phone)

HOME PAGE: http://chinchia.mit.edu

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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