Spatial Management of Distributed Social Systems

The paper describes the use of invented,developed,and tested in different countries of the high-level spatial grasp model and technology capable of solving important problems in large social systems,which may be represented as dynamic,self-evolving and distributed social networks.The approach allows us to find important solutions on a holistic level by spatial navigation and parallel pattern matching of social networks with active self-propagating scenarios represented in a special recursive language.This approach effectively hides inside the distributed and networked language implementation traditional system management routines,often providing hundreds of times shorter and simpler high-level solution code.The paper highlights the demands to efficient simulation of social systems,briefs the technology used,and provides some programming examples for solutions of practical problems.

Emerging Trends in Social Networking Systems and Generation Gap with Neutrosophic Crisp Soft Mapping

This paper aims to introduce the novel concept of neutrosophic crisp soft set(NCSS),including various types of neutrosophic crisp soft sets(NCSSs)and their fundamental operations.We define NCS-mapping and its inverse NCS-mapping between two NCS-classes.We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems(SNSs)for our various generations.We investigate the advantages,disadvantages,and natural aspects of SNSs for five generations.With the changing of the generations,it is analyzed that emerging trends and the benefits of SNSs are increasing day by day.The suggested modeling with NCS-mapping is applicable in solving various decision-making problems.

Epigenomics and gene regulation in mammalian social systems

Social epigenomics is a new field of research that studies how the social environment shapes the epigenome and how in turn the epigenome modulates behavior.We focus on describing known gene-environment interactions(GEIs)and epigenetic mechanisms in different mammalian social systems.To illustrate how epigenetic mechanisms integrate GEIs,we highlight examples where epigenetic mechanisms are associated with social behaviors and with their maintenance through neuroendocrine,locomotor,and metabolic responses.We discuss future research trajectories and open questions for the emerging field of social epigenomics in nonmodel and naturally occurring social systems.Finally,we outline the technological advances that aid the study of epigenetic mechanisms in the establishment of GEIs and vice versa.

An Approach for Personalized Social Matching Systems by Using Ant Colony

Personalized social matching systems can be seen as recommender systems that recommend people to others in the social networks, with desirable skills/characteristics. In this work, an algorithm based on Ant Colony is proposed to solve the optimization problem of clustering/matching people in a social network specifically designed for this purpose;during this process, their personal characteristics and preferences (and the degree of importance thereof) are taken into account. The numerical results indicate that the proposed algorithm can successfully perform clustering with a variable number of individuals.

Complex Systems Theory: Some Considerations for Sociology

This essay presents a reflection on the main implications of Complexity Theory for science in general, redefining and dispelling myths of traditional science, and Sociology in particular, suggesting a redefinition of Parsons’ classic concept of Social System, articulated around the property of self-maintenance of order rather than on its possible discontinuity and instability. It argues that Complexity Theory has established the limits of Classic Science, leading to a more realistic awareness of working and evolution mechanisms of Natural and Social Systems and showing the limits of our capacity to predict and control events. Dissipative structures have shown the creative role of time. Instability, emergence, surprise, unpredictability are the rule rather than the exception when systems move away from equilibrium (entropy), even if these processes are generated from a system’s deterministic working mechanisms. Therefore, we have come to realize how constructive the contribution of Complexity is, in regards to the long lasting problem of the relationship between order and disorder. Today, the terms of this relationship have been re-specified in its new configuration of inter-relationship link, according to a unicum which finds its synthesis in self-organization and deterministic chaos concepts. From this perspective, as Prigogine suggested, studies on Complex Systems are heading toward a historical, biological conception of Physics, and a new alliance between natural systems and living, social systems. Non-linearity, far from equilibrium self-organization, emergence and surprise meet at all levels, as this paper attempts to highlight. In Sociology, insights of Complexity Theory have contributed to a new way of thinking about social systems, by re-addressing some fundamental issues starting to social system, emergence and change concepts. The current social system conception as complex dynamical systems is supported by a profitable use of non-liner models (in particular, the Logistic map) in the study of social processes.

Intelligent Service Search Model Using Emerging Technologies

In recent years,the Internet of Things(IoT)has played a vital role in providing various services to users in a smart city.However,searching for services,objects,data,and frameworks remains a concern.The technological advancements in Cyber-Physical Systems(CPSs)and the Social Internet of Things(SIoT)open a new era of research.Thus,we propose a Cyber-Physical-Social Systems(CPSs)for service search.Herein,service search and object discovery operation carries with the suitable selection of friends in the network.Our proposed model constructs a graph and performs social network analysis(SNA).We suggest degree centrality,clustering,and scalefree emergence and show that a rational selection of friends per service exploration increases the overall network navigability.The efficiency of our proposed system is verified using real-world datasets based on service processing time,path length,giant component,and network diameter.The simulation results proved that our proposed system is efficient,robust,and scalable.

Social System Historical Modeling of Western Economies and its Implications for Eastern Economies

The two purposes of the research are(a)to develop an analytical model that views the economy/polity as a social system with interactive subsystems of actors:households,firms,government,political parties and other significant actors,and(b)apply the analytical model to construct and verify a timeline that figures major events in world development that shaped the evolution of the western economies,and the relative strength of their interacting subsystems.The timeline highlights the changing and evolving dominance of the major subsystems in the economic history of the western world.We differ from the convention of looking at history as the occurrence of exogenous consequential events and offer instead a system dynamics analysis that makes historical events endogenous and to be affected by the powerplay within the system.The current dominance of the firm subsystem in western countries is demonstrated to be the accumulated result of centuries of past events:wars,discoveries,colonies,trade,political enlightenments,and industrial revolutions that strengthened participation and interactions in the firm subsystem at the cost of weakened dominance of rival subsystems(those of traditional households,theocrats,manors,communes,royals,and the modern state subsystem).The behavioral orientation of a social system is explainable in terms of(a)interactive influence(which occurs during the participation and interaction of agents in multiple settings,with some settings having more interactive influence than others),and(b)regulative influence(where the conduct of the one subsystem overrules that of other subsystems).Western economic history suggests a positive conditional correlation and convergence between(a)and(b).Being conditional,the convergence between(a)and(b)may not hold in other world contexts,i.e.,China,India,Arab and African countries.

BPR-UserRec:a personalized user recommendation method in social tagging systems

Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems （STS） are becoming more and more popular for users to annotate, organize and share items on the Web. Moreover, online social network has been incorporated into social tagging systems. As more and more users tend to interact with real friends on the Web, personalized user recommendation service provided in social tagging systems is very appealing. In this paper, we propose a personalized user recommendation method, and our method handles not only the users＇ interest networks, but also the social network information. We empirically show that our method outperforms a state-of-the-art method on real dataset from Last.fro dataset and Douban.

Tag-Aware Recommender Systems:A State-of-the-Art Survey

In the past decade,Social Tagging Systems have attracted increasing attention from both physical and computer science communities.Besides the underlying structure and dynamics of tagging systems,many efforts have been addressed to unify tagging information to reveal user behaviors and preferences,extract the latent semantic relations among items,make recommendations,and so on.Specifically,this article summarizes recent progress about tag-aware recommender systems,emphasizing on the contributions from three mainstream perspectives and approaches：network-based methods,tensor-based methods,and the topic-based methods.Finally,we outline some other tag-related studies and future challenges of tag-aware recommendation algorithms.

SOCIAL TAGGING DYNAMICS UNDER SYSTEM RECOMMENDATION AND RESOURCE MULTIDIMENSIONALITY

Social tagging systems have attracted plenty of research endeavors recently. The dynamic models of tag generation or tag usage are one of the key subjects of inquiry. However, the existing models do not well explain the ＂staged＂ power-law distribution of tag usage frequencies as observed in various social tagging systems. To cope with this, a new tag-generation model is proposed in this paper, which is based on a preferential selection mechanism influenced by the combinatorial effects of system recommendation and resource multidimensionality. Furthermore, to validate the model, the simulative results under different parameter combinations are compared with the distributions of tag usage frequencies in datasets from three famous social tagging systems, namely Delicious.com, Last.fin and Flickr. For different categories of resources of the three systems, three tag usage patterns can be identified, namely the power-law distribution with two plateaus, the power-law distribution with one plateau, and the standard power-law distribution. All the three patterns can be well fitted and explained by the proposed model.

Big data technology in infectious diseases modeling,simulation,and prediction after the COVID-19 outbreak

After the outbreak of COVID-19,the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods.Starting from the research purpose and data,researchers im-proved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems.In terms of modeling methods,the researchers use compartment subdivi-sion,dynamic parameters,agent-based model methods,and artificial intelligence related methods.In terms of factors studied,the researchers studied 6 categories:human mobility,nonpharmaceutical interventions(NPIs),ages,medical resources,human response,and vaccine.The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies.This review started with a research structure of research purpose,factor,data,model,and conclusion.Focusing on the post-COVID-19 infectious disease prediction simulation research,this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.

Finite Size Effects in the Dynamics of Opinion Formation

For some models of relevance in the social sciences we review some exam-ples in which system size plays an important role in the final outcome of the dynamics.We discuss the conditions under which changes of behavior can appear only when the number of agents in the model takes a finite value.Those changes of behavior can be related to the apparent phase transitions that appear in some physical models.We show examples in the Galam's model of opinion transmission and the Axelrod's model of culture formation stressing the role that the network of interactions has on the main results of both models.Finally,we present the phenomenon of system-size stochastic resonance by which a forcing signal(identified as an advertising agent)is optimally amplified by a population of the right(intermediate)size.Our work stresses the role that the system size has in the dynamics of social systems and the inappropriateness of taking the thermodynamic limit for these systems.

Contemporary Currents in Japanese Machizukuri (Citizens Collaborative Community Improvements and Management) and Their Socio-Cultural Meanings

This paper studies the contemporary attempts of Japanese Machizukuri,Citizens Collaborative Community Improvement and Management,and their socio-cultural meanings in order to shed light on the sustainable planning approaches dealing with population ageing and decreasing.In recent years,as response measures for non-physical local issues such as environmental problems and welfare,and with the aim of further enhancing community-centred planning capabilities against a background of decentralisation in various fields and the establishment of civic society,new cooperative/collaborative-style planning theory is being deployed.Through this process,community improvement and management is becoming deeper,in terms of technology,systems,and technique.The study attempts to find out a solution to real-world problems-how to construct a comprehensive planning theory based on spatial and social challenges arising in modern civic communities,with local resources,social capital and systems that have resulted from such issues.It also seeks to show how to achieve a vision for the city as a whole by mutually compiling individual community improvement and management scenarios and programs,based on the autonomous determination and future vision of the organisations and residents that play leading roles in the community.