scholarly journals THE EFFECT OF NETWORK TYPES ON HERD BEHAVIOR

2019 ◽  
Vol 4 (8) ◽  
pp. 161-169
Author(s):  
Quji Bichia
Keyword(s):  
Preferential Attachment ◽  
Small World ◽  
Group Behavior ◽  
Human Interaction ◽  
Separate Analysis ◽  
Central Figure ◽  
Two Component ◽  
Hub Networks ◽  
Different Types ◽  
Hub Network

This paper aims to compare spread of an opinion, norm, innovation or a belief in different types of networks. For this purpose, different network metrics are discussed and results of network model are summarized based on simulations. Norms may spread from a single source or multiple sources and these issues require separate analysis. Networks play an important role in decisions that people make. They determine what information someone will receive and how will he act within this limited information. As it turns out, small number of people can influence decisions of majority. These can be consumption decision, decisions about adopting new technologies, innovations, medical practice, social norms and so on. Mathematical models of net- works help us understand how these processes propagate. There are different types of networks that can emerge within a society or some group and there are characteristics that can describe roles of group members in spreading some idea or innovation. Networks can be of many kinds but human networks tend to have common characteristics. Therefore, current work focuses on 4 types of networks - small world, single-hub (one central figure), multi-hub (many central figures) and two-component. Small world random networks are observed in different situations and they can be used to describe some human interaction networks. Many networks are described by power law distributions, where new members of a net- work have a preferential attachment and link to other highly connected members. Single-hub and multi-hub networks describe such situations. Two-component network is used to describe polarized groups that have opposing views and are competing with each other. This could be political parties or competing firms. The present paper analyzes patterns of information flow across different types of networks and compares the conditions for the emergence of group behavior. Contribution of this work is the simulation results that show how different networks exhibit varying outcomes and propagate opinions differently. Simulations on small world, single-hub, multi-hub and two-component networks with 150 members show that net- work types matter in terms of how fast can group behavior spread within a network. The process of spreading group behavior is as follows: Every individual receives some signal si about a binary decision. Individuals make the first decision based on their signals because they have no other information. In the next step, every individual looks at the decisions of those in his or her neighborhood and updates his or her belief by the Bayes rule. On the next step they observe others’ actions again and decide whether to change own action or not and so on. After some stages, a stable point is reached where no one is willing to change his decision anymore. The study compares the times needed to reach stability in different types of networks. Simulations have shown that the speed of propagation of a belief varies according to who is the source of this process. However, the difference is not big within a small world network. As it turns out, full distribution occurs in at least 4 and a maximum of 20 periods, and the average time of full distribution varies from 6.5 to 8.6, depending on whether the most connected member is the source or the least connected one. The result is quite different if there is one central figure. The presence of one central figure prevents information from spreading across the network, as there is preferential attach- ment and some members can only acquire one connection. If there are several central figures, the full spread occurs relatively faster. In a two-component network, full adoption oc- curs quite rapidly. Although the connection between components is almost non-existent, a small number of existing links play a critical role in rapidly disseminating a behavior. Group behavior spreads more rapidly in a random net- work than in a network characteristic of a special society on average. But multi-hub network has the potential for the fast- est spread (although information disseminates faster in a ran- dom network on average). Group behavior is slow to spread in a single-hub network, as some individuals are very weakly connected to other areas of the network. An opinion spread in the neighbourhood of the central figure will soon reach all members of around him or her but it will take a long time to reach far ends of the network. The two-component network in this regard maintains a balance between the speed of dis- tribution and the area of distribution. There is least variation between adoption times in a two-component network (not considering the small-world random network). The high variation in single-hub and multi-hub networks indicates that it is advisable to consider more specific situations for accurate results. Comparison of adoption times within multi-hub net- works of different size shows that adoption happens at the same speed most of the time regardless of the network size. When two opposing opinions are being spread and one of the opinions is dominated by the other, it takes similar time periods for all sizes of multi-hub networks.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Visualizing Spatial Economic Supply Chains to Enhance Sustainability and Resilience

2021 ◽  
Vol 13 (3) ◽  
pp. 1512
Author(s):  
Yicheol Han ◽  
Stephan J. Goetz ◽  
Claudia Schmidt
Keyword(s):  
Supply Chains ◽  
Preferential Attachment ◽  
Material Balance ◽  
Service Industries ◽  
Firm Location ◽  
Commodity Flows ◽  
Geographic Space ◽  
Different Types ◽  
Gravity Equations ◽  
General Method

This article presents a spatial supply network model for estimating and visualizing spatial commodity flows that used data on firm location and employment, an input–output table of inter-industry transactions, and material balance-type equations. Building on earlier work, we proposed a general method for visualizing detailed supply chains across geographic space, applying the preferential attachment rule to gravity equations in the network context; we then provided illustrations for U.S. extractive, manufacturing, and service industries, also highlighting differences in rural–urban interdependencies across these sectors. The resulting visualizations may be helpful for better understanding supply chain geographies, as well as business interconnections and interdependencies, and to anticipate and potentially address vulnerabilities to different types of shocks.

scholarly journals Politeness and reputation in cultural evolution

2020 ◽  
Author(s):  
Roland Mühlenbernd ◽  
Sławomir Wacewicz ◽  
Przemysław Żywiczyński
Keyword(s):  
Language Use ◽  
Evolutionary Dynamics ◽  
Order Theory ◽  
Evolutionary Stability ◽  
Human Interaction ◽  
Social Image ◽  
Different Types ◽  
Politeness Strategies ◽  
Higher Order Theory ◽  
Cultural Evolutionary

AbstractPoliteness in conversation is a fascinating aspect of human interaction that directly interfaces language use and human social behavior more generally. We show how game theory, as a higher-order theory of behavior, can provide the tools to understand and model polite behavior. The recently proposed responsibility exchange theory (Chaudhry and Loewenstein in Psychol Rev 126(3):313–344, 2019) describes how the polite communications of thanking and apologizing impact two different types of an agent’s social image: (perceived) warmth and (perceived) competence. Here, we extend this approach in several ways, most importantly by adding a cultural-evolutionary dynamics that makes it possible to investigate the evolutionary stability of politeness strategies. Our analysis shows that in a society of agents who value status-related traits (such as competence) over reciprocity-related traits (such as warmth), both the less and the more polite strategies are maintained in cycles of cultural-evolutionary change.

Lexical-Grammatical Status and Lexicographic Presentation of Two-Component Stable Prepositional Combinations

2021 ◽  
pp. 32-51
Author(s):  
Elena V. Generalova ◽  
Keyword(s):  
Summary Table ◽  
Complex Issue ◽  
Dictionary Entry ◽  
Figurative Meaning ◽  
Advantages And Disadvantages ◽  
Unresolved Question ◽  
Two Component ◽  
Different Types ◽  
Syntactic Properties ◽  
Theoretical Issues

The aim of the article is to review the ways of dictionary presentation of stable prepositional combinations and the factors essential for their lexical-grammatical status and the type of optimal lexicographic description. The object of the study is twocomponent prepositional combinations with stable meanings and the “preposition+noun” structure. The material of the article is data of different dictionaries of Russian presenting stable prepositional combinations. In the course of the study, the following questions were answered: why the definition and interpretation of the lexical-grammatical nature of stable prepositional combinations are so difficult and ambiguous; what lexicographic interpretation these units have in dictionaries of different types; what the advantages and disadvantages of different ways of dictionary interpretation of such language material are. The following methods were used: introspective (observation, generalization, classification), systematic lexicographic description according to dictionary parameters, dictionary definition analysis. The summary table of the lexicographic presentation of stable combinations allows seeing both the unresolved question of dictionary interpretation of such units and the patterns of their interpretation depending on the type of a dictionary. As a result of the analysis the following conclusions were drawn. 1) In modern Russian there is a rather large (about 2,000 units) class of language units (prepositional combinations), the lexical-grammatical status of which is not defined, and there is no term for their definition; this class is historically formed and continues to replenish. 2) The type of dictionary presentation of stable prepositional combinations is determined by the dictionary concept, grammatical and syntactic properties, presence of figurative meaning and possibility of component variation of such combinations. 3) The unresolved theoretical issues have as a result the lexicographic discrepancy in the presentation of these language units. Extreme lexicographic solutions are a separate dictionary entry for each combination and the presentation of such units only as stable combinations in the entry of a noun (presented in academic explanatory dictionaries). 4) Taking into account only the factor of presence/absence of a gap seems to formalize the dictionary presentation of adverbs with both conjoined and split spelling, really existing in Russian, and the position of recognition of these units with independent words and their isolate presentation is not impeccable for dictionary users. 5) In the author’s opinion, the presentation of stable prepositional combinations exclusively as independent vocabules is inferior to the traditional lexicographic approach because the isolated presentation of this material breaks the semantic connections of these complex lexical units; the most complex issue is the differentiation of adverbs with split spelling and stable combinations.

scholarly journals Monte Carlo simulations of two-component drop growth by stochastic coalescence

2008 ◽  
Vol 8 (2) ◽  
pp. 7289-7313 ◽  
Author(s):  
L. Alfonso ◽  
G. B. Raga ◽  
D. Baumgardner
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Stochastic Algorithm ◽  
Aerosol Composition ◽  
Particle Charging ◽  
Two Component ◽  
Different Types ◽  
Framework Species ◽  
Stochastic Coalescence ◽  
Good Agreement

Abstract. The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method.~The stochastic algorithm of Gillespie (1976) for chemical reactions in the formulation proposed by Laurenzi et al. (2002) was used to simulate the kinetic behavior of the drop population. Within this framework species are defined as droplets of specific size and aerosol composition. The performance of the algorithm was checked by comparing the numerical with the analytical solutions found by Lushnikov (1975). Very good agreement was observed between the Monte Carlo simulations and the analytical solution. Simulation results are presented for bi-variate constant and hydrodynamic kernels. The algorithm can be easily extended to incorporate various properties of clouds such as including several crystal habits, different types of soluble CCN, particle charging and drop breakup.

The effectiveness of treatment of patients with pulmonary tuberculosis with multiple decay cavities

1993 ◽  
Vol 74 (1) ◽  
pp. 24-28
Author(s):  
G. A. Smirnov ◽  
E. A. Martynenkova ◽  
R. M. Fattakhova ◽  
R. Sh. Valiev
Keyword(s):  
Pulmonary Tuberculosis ◽  
Clinical Course ◽  
Separate Analysis ◽  
Destructive Process ◽  
Complex Therapy ◽  
Different Types

Pulmonary tuberculosis with multiple decay cavities is classified as a common destructive process and is treated with more intensive methods. We have drawn attention to the fact that the processes with the number of cavities more than one are very different in the nature of the flow. Having accumulated a sufficient number of observations over 15 years, we decided to conduct a separate analysis of the clinical course of the disease and evaluate the effectiveness of some methods of complex therapy in different types of pulmonary tuberculosis with multiple decay cavities.

Application of Computational Intelligence Techniques in Managing Wireless Sensor Networks

2010 ◽  
pp. 39-72
Author(s):  
Ibrahiem Mahmoud Mohamed El Emary
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Management ◽  
Computational Intelligence ◽  
Critical Issue ◽  
Human Interaction ◽  
Wireless Sensor ◽  
Hierarchical Architecture ◽  
Different Types ◽  
Management Functions

This chapter gives a brief background on network management and how it is integrated into sensor network as well as the application of computational intelligence techniques in managing wireless sensor networks. Also discussed how Genetic Algorithms work in common and how they can be applied to sensor networks. Among the major management tasks rely on consumption power management, so there are many challenges associated with sensor networks but the primary challenge is energy consumption. Sensor networks are typically have little human interaction and are installed with limited battery supplies. This makes energy conservation a critical issue in deployed WSNs. All types of networks require monitoring and maintenance. A service that supplies a set of tools and applications that assist a network manager with these tasks is network management. It includes the administration of networks and all associated components. While all networks require some form of network management, different types of networks may stress certain aspects of network management. Some networks may also impose new tasks on network management. There are different types of network management architectures: centralized, hierarchical and distributed. In a centralized approach, one central server performs the role of the network management application. A hierarchical architecture will include multiple platforms, typically one server and several clients, performing network management functions.

A Novel Approach for Analyzing Single Buffer Queueing Systems with State-Dependent Vacation and Correlated Input Process under Four Different Service Disciplines

2015 ◽  
Vol 6 (3) ◽  
pp. 19-59 ◽  
Author(s):  
Thomas Yew Sing Lee
Keyword(s):  
Performance Measures ◽  
Probability Generating Function ◽  
Performance Measure ◽  
Idle Time ◽  
Separate Analysis ◽  
Input Process ◽  
State Dependent ◽  
Special Cases ◽  
Service Disciplines ◽  
Different Types

The author presents performance analysis of a single buffer multiple-queue system. Four different types of service disciplines (i.e., non-preemptive, pre-emptive repeat different, state dependent random polling and globally gated) are analyzed. His model includes correlated input process and three different types of non-productive time (i.e., switchover, vacation and idle time). Special cases of the model includes server with mixed multiple and single vacations, stopping server with delayed vacation and stopping server with alternating vacation and idle time. For each of the four service disciplines the key performance measures such as average customer waiting time, loss probability, and throughput are computed. The results permit a detailed discussion of how these performance measures depends on the customer arrival rate, the customer service time, the switchover time, the vacation time, and the idle time. Moreover, extensive numerical results are presented and the four service disciplines are compared with respect to the performance measure. Previous studies of the single buffer multiple-queue systems tend to provide separate analysis for the two cases of zero and nonzero switchover time. The author is able to provide a unified analysis for the two cases. His results generalize and improve a number of known results on single buffer multiple-queue systems. Furthermore, this method does not require differentiation while it is needed if one uses the probability generating function approach. Lastly, the author's approach works for all single buffer multiple-queue systems in which the next queue to be served is determines solely on the basis of the occupancy states at the end of the cycle time.

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 A quality-of-service-aware dynamic evolution model for space–ground integrated network

2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772864 ◽  
Author(s):  
Zhuo Yi ◽  
Xuehui Du ◽  
Ying Liao ◽  
Lifeng Cao
Keyword(s):  
Quality Of Service ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Power Law Distribution ◽  
Integrated Network ◽  
Complex Network Theory

Space–ground integrated network, a strategic, driving, and irreplaceable infrastructure, guarantees the development of economic and national security. However, its natures of limited resources, frequent handovers, and intermittently connected links significantly reduce the quality of service. To address this issue, a quality-of-service-aware dynamic evolution model is proposed based on complex network theory. On one hand, a quality-of-service-aware strategy is adopted in the model. During evolution phases of growth and handovers, links are established or deleted according to the quality-of-service-aware preferential attachment following the rule of better quality of service getting richer and worse quality of service getting poor or to die. On the other hand, dynamic handover of nodes and intermittent connection of links are taken into account and introduced into the model. Meanwhile, node heterogeneity is analyzed and heterogeneous nodes are endowed with discriminate interactions. Theoretical analysis and simulations are utilized to explore the degree distribution and its characteristics. Results reveal that this model is a scale-free model with drift power-law distribution, fat-tail and small-world effect, and drift character of degree distribution results from dynamic handover. Furthermore, this model exerts well fault tolerance and attack resistance compared to signal-strength-based strategy. In addition, node heterogeneity and quality-of-service-aware strategy improve the attack resistance and overall quality of service of space–ground integrated network.

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