TY - JOUR
T1 - Impact of Confirmation Bias on Competitive Information Spread in Social Networks
AU - Mao, Yanbing
AU - Akyol, Emrah
AU - Hovakimyan, Naira
N1 - Manuscript received August 30, 2020; revised August 31, 2020 and November 8, 2020; accepted December 18, 2020. Date of publication January 8, 2021; date of current version August 24, 2021. This work was supported in part by the National Science Foundation under Grant NSF CNS-1932529 and Grant NSF CCF-1910715, and in part by the Interdisciplinary Collaboration Grant 2019, Binghamton University-SUNY. Recommended by Associate Editor Prof. L. Schenato. (Corresponding author: Yanbing Mao.) Yanbing Mao and Naira Hovakimyan are with the Department of Mechanical Science and Engineering, University of Illinois at Urbana\u2013 Champaign, Urbana, IL 61801 USA (e-mail: [email protected]; [email protected]).
PY - 2021/6/1
Y1 - 2021/6/1
N2 - This article investigates the impact of confirmation bias on competitive information spread in the social network that comprises individuals in a social network and competitive information sources at a cyber layer. We formulate the problem of information spread as a zero-sum game, which admits a unique Nash equilibrium in pure strategies. We characterize the dependence of pure Nash equilibrium on the public's innate opinions, the social network topology, as well as the parameters of confirmation bias. We uncover that confirmation bias moves the equilibrium toward the center only when the innate opinions are not neutral, and this move does not occur for the competitive information sources simultaneously. Numerical examples in the context of well-known Krackhardt's advice network are provided to demonstrate the correctness of theoretical results.
AB - This article investigates the impact of confirmation bias on competitive information spread in the social network that comprises individuals in a social network and competitive information sources at a cyber layer. We formulate the problem of information spread as a zero-sum game, which admits a unique Nash equilibrium in pure strategies. We characterize the dependence of pure Nash equilibrium on the public's innate opinions, the social network topology, as well as the parameters of confirmation bias. We uncover that confirmation bias moves the equilibrium toward the center only when the innate opinions are not neutral, and this move does not occur for the competitive information sources simultaneously. Numerical examples in the context of well-known Krackhardt's advice network are provided to demonstrate the correctness of theoretical results.
KW - Analytical models
KW - Competitive information spread
KW - Context modeling
KW - Games
KW - Nash equilibrium
KW - Social networking (online)
KW - Steady-state
KW - Symmetric matrices
KW - confirmation bias
KW - innate opinion
KW - social network topology
KW - zero-sum game
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U2 - 10.1109/TCNS.2021.3050117
DO - 10.1109/TCNS.2021.3050117
M3 - Article
AN - SCOPUS:85099591611
SN - 2325-5870
VL - 8
SP - 816
EP - 827
JO - IEEE Transactions on Control of Network Systems
JF - IEEE Transactions on Control of Network Systems
IS - 2
ER -