Evolutionary prisoner’s dilemma on Newman-Watts social networks with an asymmetric payoff distribution mechanism

In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner＇s dilemma game （PDG） on Newman Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α： if α〉 0, the rich will exploit the poor to get richer; if α 〈 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with c~ and is remarkably promoted when c~ 〉 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system＇s wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.

CRSG:A congestion control routing algorithm for security defense based on social psychology and game theory in DTN

The inherent selfishness of each node for the enhancement of message successful delivery ratio and the network overall performance improvement are reflected in the contradiction relationship of competition and cooperation in delay/disruption tolerant networks (DTN). In particular, the existence of malicious node aggravates this contradiction. To resolve this contradiction, social relationship theory and group theory of social psychology were adopted to do an in-depth analysis. The concrete balancing approach which leveraged Nash equilibrium theory of game theory was proposed to resolve this contradiction in reality. Thus, a new congestion control routing algorithm for security defense based on social psychology and game theory (CRSG) was put forward. Through the experiment, this algorithm proves that it can enhance the message successful delivery ratio by more than 15% and reduce the congestion ratio over 15% as well. This algorithm balances the contradiction relationship between the two key performance targets and made all nodes exhibit strong cooperation relationship in DTN.

数字经济、社会信任与全国统一大市场

加快发展数字经济、推动社会信用体系与构建全国统一大市场是党的二十大报告中提到的重要现实问题。基于中国家庭追踪调查(CFPS)2018年与2020年两期平衡面板数据,识别了数字经济发展中,依托社会信任改善全国统一大市场的路径和重点难点。结果表明,数字经济发展带动了根本性的社会变迁。将数字信任引入社会信任谱系,发现数字经济可以显著提升行为主体的社会信任,有助于健全社会信用体系;异质性检验显示,数字经济对数字移民、女性与未提供家庭照料服务的个体的社会信任的促进效果更加明显。个体、家庭资源禀赋的差距会引致数字鸿沟的不利作用。另外,数字经济与社会信任的关系还会受到同伴效应以及外部环境冲击的影响;机制分析表明,数字经济可以从城乡融合(宏观)、人格特征(微观)视角拓展和丰富个体的数字化生存能力,优化个体的社会信任;进一步分析显示,数字经济可以经由社会信任强化社会互动与交换,进一步破除地方保护和市场分割,进而促进国内统一大市场的建设。研究的政策含义是,在数字经济应用场景的陆续铺设中,应将正式制度与社会信任这一非正式制度相结合,这有助于加快推进全国统一大市场的建设。研究的政策建议是,数字社会也应遵循以人为本的平等内涵,将社会信任融入数字技术应用与数据要素流转两个层面,丰富全国统一大市场建设的实践路径。

A Visual-Based Gesture Prediction Framework Applied in Social Robots

In daily life,people use their hands in various ways for most daily activities.There are many applications based on the position,direction,and joints of the hand,including gesture recognition,gesture prediction,robotics and so on.This paper proposes a gesture prediction system that uses hand joint coordinate features collected by the Leap Motion to predict dynamic hand gestures.The model is applied to the NAO robot to verify the effectiveness of the proposed method.First of all,in order to reduce jitter or jump generated in the process of data acquisition by the Leap Motion,the Kalman filter is applied to the original data.Then some new feature descriptors are introduced.The length feature,angle feature and angular velocity feature are extracted from the filtered data.These features are fed into the long-short time memory recurrent neural network(LSTM-RNN)with different combinations.Experimental results show that the combination of coordinate,length and angle features achieves the highest accuracy of 99.31%,and it can also run in real time.Finally,the trained model is applied to the NAO robot to play the finger-guessing game.Based on the predicted gesture,the NAO robot can respond in advance.

Role of Clustering Coefficient on Cooperation Dynamics in Homogeneous Networks

Based on previous works, we give further investigations on the Prisoners＇ Dilemma Game （PDG） on two different types of homogeneous networks, i.e. the homogeneous small-world network （HSWN） and the regular ring graph. We find that the so-called resonance-like character can occur on both the networks. Different from the viewpoint in previous publications, we think the small-world effect may be unnecessary to produce this character. Therefore, over these two types of networks, we suggest a common understanding in the viewpoint of clustering coefficient. Detailed simulation results can sustain our viewpoint quite well. Furthermore, we investigate the Snowdrift Game （SG） on the same networks. The difference between the outputs of the PDG and the SG can also sustain our viewpoint.

Best Response Games on Regular Graphs

With the growth of the internet it is becoming increasingly important to understand how the behaviour of players is affected by the topology of the network interconnecting them. Many models which involve networks of interacting players have been proposed and best response games are amongst the simplest. In best response games each vertex simultaneously updates to employ the best response to their current surroundings. We concentrate upon trying to understand the dynamics of best response games on regular graphs with many strategies. When more than two strategies are present highly complex dynamics can ensue. We focus upon trying to understand exactly how best response games on regular graphs sample from the space of possible cellular automata. To understand this issue we investigate convex divisions in high dimensional space and we prove that almost every division of k - 1 dimensional space into k convex regions includes a single point where all regions meet. We then find connections between the convex geometry of best response games and the theory of alternating circuits on graphs. Exploiting these unexpected connections allows us to gain an interesting answer to our question of when cellular automata are best response games.

Examining the Role of Personality Factors in Problematic Video Game Play Associated with Facebook Games

The current study used the structural components of Facebook games to select predictors of Problematic Video Game Play (PVGP) in relation to Facebook games. Based upon how game design and structure may interact with personality characteristics, the current study examined the effects of hypercompetitiveness, narcissism, reward responsiveness and psychological absorption on PVGP for a group of Facebook gamers. Moreover, the present study also observed how results may differ between Facebook gamers (n = 102), and a group of other (non-Facebook) gamers (n = 132). The Facebook group comprised 84% of females with an average age of 40.39 (SD = 14.00), whereas the other group of gamers consisted of 61% of males with an average age of 24.70 (SD = 7.86). Participants completed an online survey. Structural Equation Modelling (SEM) revealed that an interaction between hypercompetitiveness and narcissism was the only significant predictor of PVGP for Facebook gamers. In contrast, a second structural model revealed that both hypercompetitiveness and psychological absorption were significant predictors of PVGP for other types of gamers. The findings from this study had important implications regarding the structure of video games and demographic differences between Facebook Gamers and other types of gamers.

The Influence of Memetic Primers in Online Comments in Video Game Blogs

Through investigating a particular blog, several factors were found which have significant influence on reader actions. This study uses the term “memetic primers” for those styles that most often cause readers to take notice of a particular comment, remember information included in it, and take action. The memetic primers were derived in a discourse analysis. The study discovered the memetic primers using logic-of-inquire approach to the online comments. While evidence indicated that the usefulness of some primers was low, it emerged those negatively written comments where the most common impact on a comment’s volume.

基于社交网络的农业科技信息传播博弈模型探析

实施乡村振兴战略和推进农业农村现代化,离不开农业科技成果的推广应用。“互联网+”时代,社交网络为传播手段对农业科技信息推广十分有利。博弈论为农业科技信息竞争提供理论依据,协助农业科技信息传播主体在“市场争夺战”博弈中做出决策。因此,在社交网络环境下,分析社交网络、博弈论与农业科技信息服务的关系,基于社交网络构建农业科技信息竞争策略博弈模型、分析农业科技信息博弈均衡、收益函数等,揭示影响农业科技信息的因素和农业科技信息传播各主体间的利益关系,协助传播主体、传播受体做出最佳决策,实现社交网络下的农业科技信息传播水平的提升。

面向舆情治理的信息管理机制演化博弈模型

在线社交网络平台中存在的冲突信息加剧了群体观念对立,需要科学合理的管理机制来实现舆情治理。提出面向舆情治理的信息管理机制演化博弈模型,通过建立动态奖惩策略,自动化地实现冲突抑制,激活网络自我净化能力。通过引入演化博弈理论,构建基于累积前景理论的社交网络用户信息冲突演化博弈模型,使用数值模拟的方法研究9个约束条件下的18种理论应用情景的演化结果,分析了双方行为互动演化规律,得出约束条件五中博弈双方理性对待信息冲突的结论。通过建立博弈分析的系统动力学模型,对动力学演变进行分析,并在满足约束条件五的前提下对模型参数进行了详细的灵敏度分析,并为动态信息管理机制提供了实用化的策略建议。所提模型首次对利益驱动、从众心理等多种因素在舆情演化中的相互作用进行建模,演化分析结果与谣言优势传播规律相符合,证实了所提模型的合理性。所提模型为社交网络中恶意信息控制系统的开发和设计提供了重要借鉴,为舆情治理的研究实践提供了新的思路。

基于演化博弈的网络舆情涌现逻辑与城市文化形象管理

网络舆情中真假信息交互涌现,混淆视听,扰乱公共空间秩序,损害着城市文化形象。本文基于“经济人”“社会人”双重属性假设及模仿理论,构建网络舆情中引领者与追随者之间的动态演化博弈模型,借助MATLAB数值模拟仿真,开展策略演化稳定性研判和真假信息涌现分析。研究发现,“社会人”偏好下,策略演化具有鲁棒性,有益于真实消息涌现;“经济人”偏好下,演化情形对引领者的影响力、模仿成本、虚假传播及模仿风险等具有敏感性,真、假信息涌现取决于以上参数值。基于分析结果,提出选择性目标免疫、全民媒介素养教育、网络实名、树立城市文化形象危机公关意识等策略,预防舆情危机发生,助力城市文化形象管理。

Public Opinion Dissemination with Incomplete Information on Social Network: A Study Based on the Infectious Diseases Model and Game Theory

Given the fragmentation of public opinion dissemination and the lag of network users’cognition,the paper analyzes public opinion dissemination with incomplete information,which can provide reference for us to control and guide the spread of public opinion.Based on the derivative and secondary radiation of public opinion dissemination with incomplete information,the Susceptible-Susceptible-Infected-Recovered-Recovered-Infected(SSIRR-I)model is proposed.Given the interaction between users,the Deffuant opinion dynamics model and evolutionary game theory are introduced to simulate the public opinion game between dissemination and immune nodes.Finally,the numerical simulation and results analysis are given.The results reveal that the rate of opinion convergence significantly affects disseminating public opinion,which is positively correlated with the promotion effect of the dissemination node and negatively correlated with the suppression effect of the immune node of public opinion dissemination.Derivative and secondary radiations have different effects on public opinion dissemination in the early stage,but promote public opinion dissemination in the later stage.The dominant immune nodes have an apparent inhibitory effect on the spread of public opinion;nevertheless,they cannot block the dissemination of public opinion.

A Survey of Game Theory as Applied to Social Networks

Social network services can not only help people form relationships and make new friends and partners,but also assist in processing personal information,sharing knowledge,and managing social relationships.Social networks achieve valuable communication and collaboration,bring additional business opportunities,and have great social value.Research on social network problems is effective by using assumption,definition,analysis,modeling,and optimization strategies.In this paper,we survey the existing problems of game theory applied to social networks and classify their application scenarios into four categories:information diffusion,behavior analysis,community detection,and information security.Readers can clearly master knowledge application in every category.Finally,we discuss certain limitations of game theory on the basis of research in recent years and propose future directions of social network research.

厦门市网络游戏企业的空间集聚与合作网络结构

本文利用2010—2020年的厦门市网络游戏企业数据,在分析厦门市网络游戏企业时空格局演化的基础上,结合企业股权关系及投资数据研究厦门市网络游戏企业合作网络结构及其时空演化特征,结论表明:第一,在企业时空格局方面,厦门市游戏企业的空间布局呈现大集聚、小聚居的空间格局,经历了初期的集聚发展后,逐渐呈现出集聚与分散趋势并存的分布格局,企业区位选择受高等教育资源、集聚经济及交通条件影响;第二,企业间合作网络规模显著增长,合作覆盖不同企业,同时形成一定的“小世界”,网络结构由单核心向多级核心发展,最终形成“多核心”结构,老牌大型游戏厂商的核心地位越发显著;第三,企业合作网络在空间上并未伴随企业集聚而发展,随着企业的空间集聚,企业间合作网络规模显著扩张但呈现出分散化趋势,较强的合作关系多存在于老牌核心企业间,而企业集聚及溢出效应的发挥带动了部分新兴企业的发展。由此,在促成企业主体集聚的同时,挖掘企业间潜在合作关联、发挥龙头企业的主导作用,搭建相应合作平台或项目库将有利于厦门市网络游戏企业的合作网络进一步发展,进而促进产业发展水平的稳步提升。

网络群体行为的演化博弈模型与分析方法

随着社会关系网络和在线社会网络应用的不断发展,如何理解和分析群体合作行为的稳定维持和演化是社会关系网络研究中面临的最大的挑战之一.文中综述了网络群体行为和随机演化博弈模型与分析方法等方面的研究工作,介绍了可用于网络群体行为分析评价的指标和模型,总结了网络群体行为和随机演化博弈模型的若干研究和分析方法,探讨了应用随机演化博弈模型进行网络群体行为研究的可行性.基于这些讨论,展望了社会关系网络中的网络群体行为研究所面临的主要挑战.

SNS用户的社交网络游戏行为研究综述

本文通过对SNS用户玩社交网络游戏行为相关研究成果的系统分析,发现被用于社交网络游戏行为研究的理论主要有使用与满足理论、技术接受模型和心流体验理论等;社交网络游戏行为的动机主要为休闲娱乐、社交互动和自我展示;而社交网络游戏使用和持续使用的影响因素包括认知性因素、情感(体验)性因素、态度性因素、人格因素、社会性因素和技术性因素。

基于社交演化博弈的社交网络用户信息分享行为演化分析

本文基于社交演化博弈模型研究了社交网络中用户信息分享行为的合作演化.在社交演化博弈模型中,用户通过不断地模仿他关注的最成功的用户的行为策略来改进自身的短期效用,或者根据声誉调整他关注的用户来改善自身所处的声誉环境,进而改进自身的长期声誉,而用户间信息分享所构成的群体交互则使用公共品博弈进行建模.通过对社交演化博弈模型的数值仿真,揭示了用户间关注关系更新的频率、用户对声誉的追逐程度和群体放大效应在社交网络演化中的影响.同时,本文也应用了社交演化博弈模型对新浪微博进行了分析,加深了人们对社交网络中信息分享行为的合作演化的理解.

协同过滤推荐系统中的用户博弈

在以协同过滤算法为核心的推荐系统中,一个用户能否获得高质量的推荐不仅取决于用户自身是否积极地参与项目评分,还取决于其他用户是否能提供足够多的评分.由于对项目评分是需要付出成本的,理性的用户总是希望以尽可能少的评分换取高质量的推荐.该文用博弈论的方法对协同过滤系统中的用户评分行为进行分析.考虑到一个用户通常无法观察到其他用户的评分和得到的推荐,该文将用户间的交互建模为不完全信息博弈,并引入"满足均衡"的概念来分析该博弈.该文假定每个用户都对推荐质量有一个预期,当所有用户的预期都得到满足时,博弈即达到均衡.针对所建立的博弈模型,该文设计了一种均衡学习算法,该算法允许用户以逐渐增加评分数量的方式来寻找均衡策略.理论分析和仿真结果均表明,当所有用户对推荐质量有着相似的预期时,所提算法可收敛到满足均衡.这一分析结果可以为协作式系统中激励机制的设计提供启发.

社交网络信息传播的博弈模型

对社交网络信息传播规律和传播过程的研究,目前主要有实证分析、数理模型和传播动力学三种理论或方法.应用博弈论的思想,从微观个体的角度出发,将关系层次作为重要变量加入到模型中,分析社交网络用户传播信息时的成本、收益和策略选择.结论认为:只要传播信息的收益大于成本,用户都会选择传播信息;用户之间的关系越紧密,越容易相互传播信息和共谋;非共谋行为并不是一个纳什均衡策略.并分析了用户的混合策略纳什均衡,使研究更接近现实,对社交网络用户信息传播的决策具有一定指导意义.

社会网络与创新扩散的共生演化

在基于协调博弈和动态网络的基础上,构建了一个社会网络与创新扩散的共生演化模型,采用仿真与计量相结合的方法,分析了创新扩散、网络整体收益和社会网络之间的相互影响。研究表明,个体行为与社会网络结构对创新扩散的影响,取决于创新自身相对优势的大小,具有相对优势的创新在密集的网络中和规则连接方式下更容易扩散。网络整体收益不仅与创新自身以及采用个体的自身特征有关,也与局部网络效应强弱和个体之间建立联系的成本相关。创新扩散微观层面中个体策略选择行为特征会导致社会网络结构特征(如网络异质性、小世界效应,度相关性)的变化。