13 research outputs found
Panic buying pada pandemi COVID-19: Telaah literatur dari perspektif psikologi
Pandemik COVID-19 memiliki berdampak pada kesehatan, sosial, ekonomi, hingga psikologis. Salah satu dampak dari COVID-19 adalah panic buying. Artikel ini bertujuan mengulas panic buying melalui perspektif psikologi. Kami melakukan telaah literatur panic buying pada riset-riset terkini baik pada kasus pandemik COVID-19 hingga pandemik serupa yang terjadi pada puluhan tahun silam. Pada bagian awal, artikel ini membandingkan definisi panic buying dengan istilah serupa, seperti buying frenzies, impulsive buying, dan compulsive buying. Kemudian, kami mengulas penjelasan psikologis di balik panic buying melalui perilaku konsumen, ketakutan dan kecemasan, stres, ketidakpastian, dan paparan media. Pada bagian terakhir, kami mengajukan beberapa solusi yang dapat dijadikan panduan kebijakan untuk mengatasi panic buying saat wabah pandemik terjadi. 
Macroscopic Noisy Bounded Confidence Models with Distributed Radical Opinions
In this article, we study the nonlinear Fokker-Planck (FP) equation that
arises as a mean-field (macroscopic) approximation of bounded confidence
opinion dynamics, where opinions are influenced by environmental noises and
opinions of radicals (stubborn individuals). The distribution of radical
opinions serves as an infinite-dimensional exogenous input to the FP equation,
visibly influencing the steady opinion profile. We establish mathematical
properties of the FP equation. In particular, we (i) show the well-posedness of
the dynamic equation, (ii) provide existence result accompanied by a
quantitative global estimate for the corresponding stationary solution, and
(iii) establish an explicit lower bound on the noise level that guarantees
exponential convergence of the dynamics to stationary state. Combining the
results in (ii) and (iii) readily yields the input-output stability of the
system for sufficiently large noises. Next, using Fourier analysis, the
structure of opinion clusters under the uniform initial distribution is
examined. Specifically, two numerical schemes for identification of
order-disorder transition and characterization of initial clustering behavior
are provided. The results of analysis are validated through several numerical
simulations of the continuum-agent model (partial differential equation) and
the corresponding discrete-agent model (interacting stochastic differential
equations) for a particular distribution of radicals
Micro-macro dynamics of the online opinion evolution: an asynchronous network model approach
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper investigates the complex relationship between endogenous and exogenous, deterministic and stochastic stimulating factors in public opinion dynamics. An asynchronous multi-agent network model is proposed to explore the interaction mechanism between individual opinions and the public opinion in online multi-agent network community, including both the micro and the macro patterns of opinion evolution. In addition, based on random network models, a novel algorithm is provided for opinion evolution prediction. The model property analysis and numerical experiments show that the proposed asynchronous multi-agent network model can assimilate and explain some interesting phenomena that are observed in the real world. Further case studies with numerical simulation and real-world applications confirm the feasibility and flexibility of the proposed model in public opinion analysis. The results challenge the common perception that mass media or opinion facilitators play the fundamental role in controlling the development trends of public opinion. This study shows that the formation and evolution of public opinion in the presence of opinion leaders depend also on an individual’s emotional inertia and conformity pressures from peers in the same topic group
Consensus Reaching in Social Network Group Decision Making: Research Paradigms and Challenges
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In social network group decision making (SNGDM), the consensus reaching process (CRP) is used to help decision makers with social relationships reach consensus. Many CRP studies have been conducted in SNGDM until now. This paper provides a review of CRPs in SNGDM, and as a result it classifies them into two paradigms: (i) the CRP paradigm based on trust relationships, and (ii) the CRP paradigm based on opinion evolution. Furthermore, identified research challenges are put forward to advance this area of research