scholarly journals How to plug out of the networks in jeopardy of ASF, Covid-19, social media or markets toxicity

E-methodology ◽  
2021 ◽  
Vol 7 (7) ◽  
pp. 71-84
Author(s):  
ANDRZEJ BUDA ◽  
KATARZYNA KUŹMICZ
Keyword(s):  
Social Media ◽  
Preferential Attachment ◽  
Global Network ◽  
Epidemic Threshold ◽  
Agent Based ◽  
Scale Free ◽  
Nearest Neighbours ◽  
Fully Connected ◽  
Node Removal ◽  
Parameter Values

Aim: In our research, we examine universal properties of the global network whose structure represents a real-world network that might be later extended to social media, commodity market or countries under the infl uence of diseases like Covid-19 or ASF.Methods: We propose quasi-epidemiological agent-based model of virus spread on a network. Firstly, we consider countries represented by subnetworks that have a scale-free structure achieved by the preferential attachment construction with a node hierarchy and binary edges. The global network of countries is a complete, directed, weighted network of thesesubnetworks connected by their capitals and divided into cultural and geographical proximity. Viruses with a defi ned strength or aggressiveness occur independently at one of the nodes of a selected subnetwork and correspond to a piece of products or messages or diseases.Results and conclusion: We analyse dynamics set by varying parameter values and observe a variety of phenomena including local and global pandemics and the existence of an epidemic threshold in the subnetworks. These phenomena have been also shown fromindividual users points of view because the node removal from the network might have impact on its nearest neighbours differently. The selective participation in global network is proposed here to avoid side effects when the global network has been fully connected and no longer divided into clusters.

Effect of connection on transport between scale free networks

2017 ◽  
Vol 28 (05) ◽  
pp. 1750064 ◽  
Author(s):  
A. Ould Baba ◽  
O. Bamaarouf ◽  
A. Rachadi ◽  
H. Ez-Zahraouy
Keyword(s):  
Numerical Simulations ◽  
Power Law ◽  
Preferential Attachment ◽  
Electrical Conductance ◽  
Global Network ◽  
Scale Free ◽  
Scale Free Networks ◽  
Conductance Distribution

Using numerical simulations, we investigate the effects of the connectivity and topologies of network on the quality of transport between connected scale free networks. Hence, the flow as the electrical conductance between connected networks is calculated. It is found that the conductance distribution between networks follow a power law [Formula: see text] where [Formula: see text] is the exponent of the global Network of network, we show that the transport in the symmetric growing preferential attachment connection is more efficient than the symmetric static preferential attachment connection. Furthermore, the differences of transport and networks communications properties in the different cases are discussed.

Epidemic spreading on evolving networks

2019 ◽  
Vol 33 (23) ◽  
pp. 1950266 ◽  
Author(s):  
Jin-Xuan Yang
Keyword(s):  
Preferential Attachment ◽  
Small World ◽  
Network Evolution ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Scale Free ◽  
Evolving Networks ◽  
Power Law Exponent ◽  
Free Network ◽  
Over Time

Network structure will evolve over time, which will lead to changes in the spread of the epidemic. In this work, a network evolution model based on the principle of preferential attachment is proposed. The network will evolve into a scale-free network with a power-law exponent between 2 and 3 by our model, where the exponent is determined by the evolution parameters. We analyze the epidemic spreading process as the network evolves from a small-world one to a scale-free one, including the changes in epidemic threshold over time. The condition of epidemic threshold to increase is given with the evolution processes. The simulated results of real-world networks and synthetic networks show that as the network evolves at a low evolution rate, it is more conducive to preventing epidemic spreading.

scholarly journals Correlated disasters and need-based transfers: The limits of risk pooling systems in simulated ecologies

2017 ◽  
Author(s):  
Marco Campenni ◽  
Lee Cronk ◽  
Athena Aktipis
Keyword(s):  
Preferential Attachment ◽  
Management Strategies ◽  
Small World ◽  
Agent Based ◽  
Risk Pooling ◽  
Risk Management Strategies ◽  
Pooling Strategies ◽  
Regular Networks ◽  
Recipient Need ◽  
Parameter Values

ABSTRACTThroughout their evolutionary history, humans have faced risks including drought, disease, natural disasters and other unexpected negative events. To deal with these risks, humans use a variety of risk management strategies, some of which involve relying on others in times of need in order to pool risk. However, the effectiveness of risk pooling strategies can be limited when there is high synchronicity of need. Here we investigate the limits of two resource transfer systems for pooling risk (need-based transfers, NBT, and debt-based transfers, DBT) in simulated ecologies with different degrees of correlated disasters using an agent-based model of the need-based transfer system of the Maasai. Overall, we find that survival is higher when shocks are less correlated among partners, when groups are larger, and when network structure is characterized by preferential attachment networks, which have a more modular structure than regular or small world networks. We also find that NBT strategies consistently outperform DBT strategies across a wide variety of parameter values and that the advantage of NBT over DBT is greatest when shocks are less correlated and group size is small. Our results also suggest that systems of sharing that are based on recipient need are less vulnerable than systems that are based on debt and credit, especially in small world and regular networks.

scholarly journals Diffusion and persistence of false rumors in social media networks: implications of searchability on rumor self-correction on Twitter

2021 ◽  
Author(s):  
Kathrin Eismann
Keyword(s):  
Social Media ◽  
Agent Based ◽  
Social Media Networks ◽  
Agent Based Simulations

AbstractSocial media networks (SMN) such as Facebook and Twitter are infamous for facilitating the spread of potentially false rumors. Although it has been argued that SMN enable their users to identify and challenge false rumors through collective efforts to make sense of unverified information—a process typically referred to as self-correction—evidence suggests that users frequently fail to distinguish among rumors before they have been resolved. How users evaluate the veracity of a rumor can depend on the appraisals of others who participate in a conversation. Affordances such as the searchability of SMN, which enables users to learn about a rumor through dedicated search and query features rather than relying on interactions with their relational connections, might therefore affect the veracity judgments at which they arrive. This paper uses agent-based simulations to illustrate that searchability can hinder actors seeking to evaluate the trustworthiness of a rumor’s source and hence impede self-correction. The findings indicate that exchanges between related users can increase the likelihood that trustworthy agents transmit rumor messages, which can promote the propagation of useful information and corrective posts.

scholarly journals Scale free is not rare in international trade networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linqing Liu ◽  
Mengyun Shen ◽  
Chang Tan
Keyword(s):  
International Trade ◽  
Preferential Attachment ◽  
Developed Countries ◽  
Total Trade ◽  
Trade Networks ◽  
Scale Free ◽  
Weighted Networks ◽  
Free Exploration ◽  
Technology Products ◽  
Attachment Mechanism

AbstractFailing to consider the strong correlations between weights and topological properties in capacity-weighted networks renders test results on the scale-free property unreliable. According to the preferential attachment mechanism, existing high-degree nodes normally attract new nodes. However, in capacity-weighted networks, the weights of existing edges increase as the network grows. We propose an optimized simplification method and apply it to international trade networks. Our study covers more than 1200 product categories annually from 1995 to 2018. We find that, on average, 38%, 38% and 69% of product networks in export, import and total trade are scale-free. Furthermore, the scale-free characteristics differ depending on the technology. Counter to expectations, the exports of high-technology products are distributed worldwide rather than concentrated in a few developed countries. Our research extends the scale-free exploration of capacity-weighted networks and demonstrates that choosing appropriate filtering methods can clarify the properties of complex networks.

scholarly journals Reproducing scientists’ mobility: a data-driven model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giacomo Vaccario ◽  
Luca Verginer ◽  
Frank Schweitzer
Keyword(s):  
Decision Rules ◽  
Migration Policy ◽  
Large Data ◽  
Global Scale ◽  
Global Network ◽  
Data Sets ◽  
Mobility Patterns ◽  
Agent Based ◽  
Hiring Process ◽  
Geographical Distances

AbstractHigh skill labour is an important factor underpinning the competitive advantage of modern economies. Therefore, attracting and retaining scientists has become a major concern for migration policy. In this work, we study the migration of scientists on a global scale, by combining two large data sets covering the publications of 3.5 million scientists over 60 years. We analyse their geographical distances moved for a new affiliation and their age when moving, this way reconstructing their geographical “career paths”. These paths are used to derive the world network of scientists’ mobility between cities and to analyse its topological properties. We further develop and calibrate an agent-based model, such that it reproduces the empirical findings both at the level of scientists and of the global network. Our model takes into account that the academic hiring process is largely demand-driven and demonstrates that the probability of scientists to relocate decreases both with age and with distance. Our results allow interpreting the model assumptions as micro-based decision rules that can explain the observed mobility patterns of scientists.

scholarly journals Agent Based Model of Anti-Vaccination Movements: Simulations and Comparison with Empirical Data

Vaccines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 809
Author(s):  
Pawel Sobkowicz ◽  
Antoni Sobkowicz
Keyword(s):  
Social Media ◽  
Critical Parameters ◽  
Rational Approach ◽  
The Internet ◽  
High Temporal Resolution ◽  
Nonlinear Feedback ◽  
Agent Based Model ◽  
Linear Processes ◽  
Agent Based ◽  
The Social

Background: A realistic description of the social processes leading to the increasing reluctance to various forms of vaccination is a very challenging task. This is due to the complexity of the psychological and social mechanisms determining the positioning of individuals and groups against vaccination and associated activities. Understanding the role played by social media and the Internet in the current spread of the anti-vaccination (AV) movement is of crucial importance. Methods: We present novel, long-term Big Data analyses of Internet activity connected with the AV movement for such different societies as the US and Poland. The datasets we analyzed cover multiyear periods preceding the COVID-19 pandemic, documenting the behavior of vaccine related Internet activity with high temporal resolution. To understand the empirical observations, in particular the mechanism driving the peaks of AV activity, we propose an Agent Based Model (ABM) of the AV movement. The model includes the interplay between multiple driving factors: contacts with medical practitioners and public vaccination campaigns, interpersonal communication, and the influence of the infosphere (social networks, WEB pages, user comments, etc.). The model takes into account the difference between the rational approach of the pro-vaccination information providers and the largely emotional appeal of anti-vaccination propaganda. Results: The datasets studied show the presence of short-lived, high intensity activity peaks, much higher than the low activity background. The peaks are seemingly random in size and time separation. Such behavior strongly suggests a nonlinear nature for the social interactions driving the AV movement instead of the slow, gradual growth typical of linear processes. The ABM simulations reproduce the observed temporal behavior of the AV interest very closely. For a range of parameters, the simulations result in a relatively small fraction of people refusing vaccination, but a slight change in critical parameters (such as willingness to post anti-vaccination information) may lead to a catastrophic breakdown of vaccination support in the model society, due to nonlinear feedback effects. The model allows the effectiveness of strategies combating the anti-vaccination movement to be studied. An increase in intensity of standard pro-vaccination communications by government agencies and medical personnel is found to have little effect. On the other hand, focused campaigns using the Internet and social media and copying the highly emotional and narrative-focused format used by the anti-vaccination activists can diminish the AV influence. Similar effects result from censoring and taking down anti-vaccination communications by social media platforms. The benefit of such tactics might, however, be offset by their social cost, for example, the increased polarization and potential to exploit it for political goals, or increased ‘persecution’ and ‘martyrdom’ tropes.

scholarly journals MARKET STATISTICS OF A PSYCHOLOGY-BASED HETEROGENEOUS AGENT MODEL

2008 ◽  
Vol 11 (07) ◽  
pp. 717-737 ◽  
Author(s):  
HARBIR LAMBA ◽  
TIM SEAMAN
Keyword(s):  
Heterogeneous Agent ◽  
Agent Based ◽  
Agent Model ◽  
Fundamental Parameters ◽  
Market Participants ◽  
Information Stream ◽  
Momentum Trading ◽  
Real Market ◽  
Available Information ◽  
Parameter Values

We continue an investigation into a class of agent-based market models that are motivated by a psychologically-plausible form of bounded rationality. Some of the agents in an otherwise efficient hypothetical market are endowed with differing tolerances to the tension caused by being in the minority. This herding tendency may be due to purely psychological effects, momentum-trading strategies, or the rational response to perverse marketplace incentives. The resulting model has the important properties of being both very simple and insensitive to its small number of fundamental parameters. While it is most certainly a caricature market, with only boundedly rational traders and the globally available information stream being modeled directly, other market participants and effects are indirectly replicated. We show that all of the most important "stylized facts" of real market statistics are reproduced by this model. Another useful aspect of the model is that, for certain parameter values, it reduces to a standard efficient-market system. This allows us to isolate and observe the effects of particular kinds of non-rationality. To this end, we consider the effects of different asymmetries in agent behavior and show that one in particular leads to skew statistics consistent with those seen in some real financial markets.

scholarly journals Testing temporal changes in allele frequencies: a simulation approach

2010 ◽  
Vol 92 (4) ◽  
pp. 309-320 ◽  
Author(s):  
EDSON SANDOVAL-CASTELLANOS
Keyword(s):  
Molecular Data ◽  
Temporal Changes ◽  
Allele Frequencies ◽  
Small Populations ◽  
Simulation Approach ◽  
Simulation Test ◽  
Agent Based ◽  
Binomial Sampling ◽  
Molecular Databases ◽  
Parameter Values

SummaryAnalysis of the temporal variation in allele frequencies is useful for studying microevolutionary processes. However, many statistical methods routinely used to test temporal changes in allele frequencies fail to establish a proper hypothesis or have theoretical or practical limitations. Here, a Bayesian statistical test is proposed in which the distribution of the distances among sampling frequencies is approached with computer simulations, and hypergeometric sampling is considered instead of binomial sampling. To validate the test and compare its performance with other tests, agent-based model simulations were run for a variety of scenarios, and two real molecular databases were analysed. The results showed that the simulation test (ST) maintained the significance value used (α=0·05) for a vast combination of parameter values, whereas other tests were sensitive to the effect of genetic drift or binomial sampling. The differences between binomial and hypergeometric sampling were more complex than expected, and a novel effect was described. This study suggests that the ST is especially useful for studies with small populations and many alleles, as in microsatellite or sequencing molecular data.

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