Heterogeneity, judgment, and social trust of agents in rumor spreading
Peng Lu
Applied Mathematics and Computation, 2019, vol. 350, issue C, 447-461
Abstract:
As one of the typical collective actions or cooperative behaviors of human beings, the rumor is widespread and harmful in the society for most cases. Modeling and predicting the dynamics and evolutions or rumors’ spreading has been widely investigated in existing models, including the (expanded) SIR models. In this paper, a micro-model of neighborhood interactions between agents (ABM) is proposed to explore the mechanism of rumors’ spreading. In the proposed model, the agents (sources or receptors) interact with the neighbors on a square lattice, and the source spreads rumors to receptors, and if the receptors decide to spread rumors they become sources as well. For each agent, the individual judgment heterogeneity and social trust heterogeneity are introduced, and the distance to the original source provides the basic field function. Distance, judgment, and trust consist of the thresholds that should be overcome before the rumor can be spread by certain agent to others. The heard time records the frequency that the rumor is heard, and the agent spreads the rumor if the heard time satisfies the threshold condition. As the mean effects of individual judgment and social trust on rumors’ spreading are stabilized, this paper focuses on their heterogeneity effects. The spreading curves monitors the instant spreading percentage and they have two stages, which are the “rapidly increase stage” with the linear relationship and “slowly increase stage” with the nonlinear relationship. Simulation outcome indicate that heterogeneity promotes the spreading while the homogeneity dampens it. Besides, the conditional effects of social trust heterogeneity under individual judgment heterogeneity coincide with the general effects. This work paves the way for the full-process prediction of rumors’ spreading.
Keywords: Rumor spreading; Simulation; Heterogeneity; Agent-based modeling; Collective actions (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300318309536
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:350:y:2019:i:c:p:447-461
DOI: 10.1016/j.amc.2018.10.079
Access Statistics for this article
Applied Mathematics and Computation is currently edited by Theodore Simos
More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().