Modelling opinion dynamics under the impact of influencer and media strategies

被引:17
作者
Helfmann, Luzie [1 ,2 ]
Conrad, Natasa Djurdjevac [1 ]
Lorenz-Spreen, Philipp [3 ]
Schuette, Christof [1 ,4 ]
机构
[1] Zuse Inst Berlin, Dept Modelling & Simulat Complex Proc, D-14195 Berlin, Germany
[2] Potsdam Inst Climate Impact Res, Complex Sci, D-14473 Potsdam, Germany
[3] Max Planck Inst Human Dev, Ctr Adapt Rat, D-14195 Berlin, Germany
[4] Free Univ Berlin, Dept Math & Comp Sci, D-14195 Berlin, Germany
关键词
TRANSITION;
D O I
10.1038/s41598-023-46187-9
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Digital communication has made the public discourse considerably more complex, and new actors and strategies have emerged as a result of this seismic shift. Aside from the often-studied interactions among individuals during opinion formation, which have been facilitated on a large scale by social media platforms, the changing role of traditional media and the emerging role of "influencers" are not well understood, and the implications of their engagement strategies arising from the incentive structure of the attention economy even less so. Here we propose a novel framework for opinion dynamics that can accommodate various versions of opinion dynamics as well as account for different roles, namely that of individuals, media and influencers, who change their own opinion positions on different time scales. Numerical simulations of instances of this framework show the importance of their relative influence in creating qualitatively different opinion formation dynamics: with influencers, fragmented but short-lived clusters emerge, which are then counteracted by more stable media positions. The framework allows for mean-field approximations by partial differential equations, which reproduce those dynamics and allow for efficient large-scale simulations when the number of individuals is large. Based on the mean-field approximations, we can study how strategies of influencers to gain more followers can influence the overall opinion distribution. We show that moving towards extreme positions can be a beneficial strategy for influencers to gain followers. Finally, our framework allows us to demonstrate that optimal control strategies allow other influencers or media to counteract such attempts and prevent further fragmentation of the opinion landscape. Our modelling framework contributes to a more flexible modelling approach in opinion dynamics and a better understanding of the different roles and strategies in the increasingly complex information ecosystem.
引用
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页数:12
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