Human settlement's social network analysis based on spatial trend surface model:a case study of Chongqing Municipality

Integrated with GIS and remote sensing(RS) technology,a systematic analysis and its methodology for human-settlements social environment has been introduced.This methodology has been called spatial trend field model(STFM).STFM's application history in the field of human-settlements social environment has been discussed at first.Then,some index data models have been created through STFM,which include population density trend field,human activity strength trend field,city-town spatial density trend field,urbanization ratio trend field,road density trend field,GDP spatial density trend field and PER-GDP spatial density trend field.With all above-mentioned indexes as input data,through Iterative Self-Organizing Data Analysis Techniques Algorithm(ISODATA),this paper makes a verification study of Chongqing municipality.The result of the case study confirms that STFM methodology is credible and has high efficiency for regional human-settlements study.

Human Interaction Dynamics for Its Use in Mobile Robotics:Impedance Control for Leader-follower Formation

A complete characterization of the behavior in human-robot interactions(HRI) includes both: the behavioral dynamics and the control laws that characterize how the behavior is regulated with the perception data. In this way, this work proposes a leader-follower coordinate control based on an impedance control that allows to establish a dynamic relation between social forces and motion error. For this, a scheme is presented to identify the impedance based on fictitious social forces, which are described by distance-based potential fields.As part of the validation procedure, we present an experimental comparison to select the better of two different fictitious force structures. The criteria are determined by two qualities: least impedance errors during the validation procedure and least parameter variance during the recursive estimation procedure.Finally, with the best fictitious force and its identified impedance,an impedance control is designed for a mobile robot Pioneer 3AT,which is programmed to follow a human in a structured scenario.According to results, and under the hypothesis that moving like humans will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction.

Recent Advances in the Modelling and Analysis of Opinion Dynamics on Influence Networks

A fundamental aspect of society is the exchange and discussion of opinions between individuals, occurring in situations as varied as company boardrooms, elementary school classrooms and online social media. After a very brief introduction to the established results of the most fundamental opinion dynamics models, which seek to mathematically capture observed social phenomena, a brief discussion follows on several recent themes pursued by the authors building on the fundamental ideas. In the first theme, we study the way an individual′s self-confidence can develop through contributing to discussions on a sequence of topics, reaching a consensus in each case,where the consensus value to some degree reflects the contribution of that individual to the conclusion. During this process, the individuals in the network and the way they interact can change. The second theme introduces a novel discrete-time model of opinion dynamics to study how discrepancies between an individual′s expressed and private opinions can arise due to stubbornness and a pressure to conform to a social norm. It is also shown that a few extremists can create "pluralistic ignorance", where people believe there is majority support for a position but in fact the position is privately rejected by the majority. Last, we consider a group of individuals discussing a collection of logically related topics. In particular, we identify that for topics whose logical interdependencies take on a cascade structure,disagreement in opinions can occur if individuals have competing and/or heterogeneous views on how the topics are related, i.e., the logical interdependence structure varies between individuals.

A dynamic influence model of social network hotspot based on grey system

The outbreak of hotspot in social network may contain complex dynamic genesis. Using user behavior data from hotspots in social network, we study how different user groups play different roles for a hotspot topic. Firstly, by analyzing users' behavior records, we mine group situation that promotes the hotspot.Several major attributions in a hotspot outbreak, such as individual, peer and group triggers, are defined formally according to the view-point of social identity, social interaction, retweet depth and opinion leader. Secondly,for the problem of the uneven and sparse data in each stage of hotspot topic's life cycle, we propose a dynamic influence model based on grey system to formalize the effect of different groups. Then the process of hotspot evolution driven by distinct crowd is showed dynamically. The experimental result confirms that the model is able not only to qualify users' influence on a hotspot topic but also to predict effectively an upcoming change in a hotspot topic.

油气管道事故原因分类模型及其社会网络分析

为提高油气管道事故预防策略的有效性,首先,基于系统理论事故建模与过程(STAMP)模型及人为因素分析与分类系统(HFACS)模型,建立油气管道事故预防控制结构,分析国内外35起油气管道事故原因,并依据扎根理论对分析结果进行统计编码,得出油气管道事故原因分类模型;其次,应用社会网络分析法构建油气管道事故原因关系网络,通过核心—边缘分析、中心性分析和关联方向指数分析,识别油气管道事故原因中核心及具有高关联性和强影响力因素。研究结果表明:油气管道事故原因分类模型包含6个层次:政府及监管部门因素、第三方因素、运营商组织因素、运营商不安全监督、现场人员不安全行为的前提条件、现场人员的不安全行为,并可将其细分为22个最底层原因因素。其中,政府及监管部门因素、运营商组织因素、运营商不安全监督和第三方因素均为核心因素;制度缺陷、监督不充分、运行计划不当、第三方破坏行为、管材与焊缝缺陷、施工/维修/配件问题、技能失误均为具有高关联性和强影响力因素。

强制性社会责任报告披露政策的规制效用评估——基于同伴效应的视角

企业社会责任信息披露有助于缓解信息不对称并约束其失范行为,提升企业合规治理质效。本文基于同伴效应视角,利用动态网络处理效应模型测度强制性社会责任报告披露政策的直接影响和同伴效应,并引入多种社交网络进行对比研究。以2003—2021年我国沪深A股上市公司为样本的实证研究表明,该政策实施的影响是其直接干预效应和社交网络下形成的同伴效应的总和。忽视同伴效应,会导致政策实施的直接干预效应被高估,总效应被低估。同时,相较于机构投资者网络和兼职独立董事网络,依据行业分类构建的同行业网络的渠道作用不稳定;政策效应评估显示,兼职独立董事网络的传导效率较高。此外,相较于经营交易违规,该政策对企业信息披露违规的治理效果更突出。本文研究表明在国家政策的制度力量之外,社交网络下的同伴学习机制有助于激励企业将社会责任的承担与履行内化为决策思维和责任基因,形成自觉防控合规风险、持续提升治理效能的内在利益动力和内生发展需求。

A Class of Rumor Spreading Models with Population Dynamics

Based on the characteristics of rumor spreading in online social networks, this paper proposes a new rumor spreading model. This is an improved SIS rumor spreading model in online social networks that combines the transmission dynamics and population dynamics with consideration of the impact of both of the changing number of online social network users and different levels of user activity. We numerically simulate the rumor spreading process. The results of numerical simulation show that the improved SIS model can successfully characterize the rumor spreading behavior in online social networks. We also give the effective strategies of curbing the rumor spreading in online social networks.

Formidable females redux:male social integration into female networks and the value of dynamic multilayer networks

The development of multilayer network techniques is a boon for researchers who wish to understand how different interaction layers might influence each other,and how these in turn might influence group dynamics.Here,we investigate how integration between male and female grooming and aggression interaction networks influences male power trajectories in vervet monkeys Chlorocebus pygerythrus.Our previous analyses of this phenomenon used a monolayer approach,and our aim here is to extend these analyses using a dynamic multilayer approach.To do so,we constructed a temporal series of male and female interaction layers.We then used a multivariate multilevel autoregression model to compare cross-lagged associations between a male's centrality in the female grooming layer and changes in male Elo ratings.Our results confirmed our original findings:changes in male centrality within the female grooming network were weakly but positively tied to changes in their Elo ratings.However,the multilayer network approach offered additional insights into this social process,identifying how changes in a male's centrality cascade through the other network layers.This dynamic view indicates that the changes in Elo ratings are likely to be short-lived,but that male centrality within the female network had a much stronger impact throughout the multilayer network as a whole,especially on reducing intermale aggression(i.e.,aggression directed by males toward other males).We suggest that multilayer social network approaches can take advantage of increased amounts of social data that are more commonly collected these days,using a variety of methods.Such data are inherently multilevel and multilayered,and thus offer the ability to quantify more precisely the dynamics of animal social behaviors.

微博社区中用户行为特征及其机理研究

基于微博数据的实证分析表明,微博用户发布微博的数量及时间间隔均服从幂律分布。通过分析微博用户之间的社会网络关系与用户行为之间的联系,发现微博消息数量的分布幂指数与用户互动指数呈反向关系,且随着互动指数的升高,幂指数的下降趋缓。在排除用户之间的评论、转发行为的影响后,个体用户发微博的时间间隔分布幂指数与用户互动指数呈正相关关系。基于上述实证分析,引入用户间评论转发行为、用户间的社会网络关系作为微博用户行为的驱动因素,提出了一种基于社会关系的动力学模型,模型仿真结果与实际数据一致。

社交网络蠕虫仿真建模研究

随着互联网虚拟社交网络的发展,借助网络用户进行传播的社交网络蠕虫已经成为威胁网络安全的重大隐患之一.文中从社会工程学的角度研究社交网络蠕虫的传播机制,通过量化影响用户行为的若干因素,提出了微观节点上的基于用户安全意识的行为博弈模型;通过分析网络用户活动的习惯特性,构建了宏观网络上离散的基于用户习惯的社交网络访问模型;从而实现了一个适用于社交网络蠕虫传播研究的仿真系统.实验分析了模型中用户相关因素对蠕虫传播的影响,验证了仿真系统的有效性.最后,利用该系统仿真了社交网络蠕虫在异质社交网络中的传播,揭示了网络拓扑结构和社交网络混杂程度对蠕虫传播的影响,为社交网络蠕虫相关研究提供了重要支持.

基于人类动力学的在线社交网络信息传播研究

Web2.0时代,社交网络因其交互性和即时性,已成为人类社会中社会关系维系和信息传播的重要载体。因此,理解社交网络用户行为特征及其对在线信息传播的影响至关重要。该文从人类行为动力学视角出发,系统梳理了近年来社交网络用户行为的实证研究。其次,综述了社交网络信息传播中用户行为时间特征的实证研究。最后,对用户行为时间特征与在线社交网络信息传播的相互作用进行了总结和展望。

计算机网络病毒传播模型SIRH

计算机网络病毒传播模型是研究计算机网络病毒的手段和工具。SIR模型是仿照生物流行病传播机制而建立的病毒传播模型。本文从计算机网络病毒传播的实际情况出发,通过分析SIR模型的不足,提出了一种在计算机网络中具有病毒防范、病毒免疫措施的网络病毒传播模型。SIRH考虑了网络病毒重复感染这种人为因素对网络病毒传播的影响。仿真实验验证了SIRH的有效合理性。

成本控制下的快速影响最大化算法

针对成本控制下影响最大化时间复杂度高的问题,提出一种快速的最大化算法BCIM。首先提出对初始节点进行多次传播的传播模型;其次选择高影响力节点作为备用种子,并基于近距离影响减少计算节点影响范围的工作量;最后利用动态规划方法在每组备用种子中最多选择一个种子。仿真实验表明,与随机算法Random、每轮取影响力增量最大的节点的贪心算法Greedy_MII、每轮取影响力增量与成本比值最大的节点的贪心算法Greedy_MICR相比,在影响范围上,BICM接近或优于Greedy_MICR及Greedy_MII,远次于Random;在种子集合的质量上,BCIM、Greedy_MICR、Greedy_MII三者差距较小,但都远远好于Random;在运行时间上,BCIM是Random的几倍,而两个贪心算法都是BCIM的几百倍。BCIM算法能在较短时间内找到更有效的种子集合。

组织内派系形成的网络动态分析

本文以行动者的模拟模型考察公司中的雇员形成派系的过程。基于互惠原则与资源交换理论,模型展示了互助行为使人与人之间产生连带,逐渐形成在内部相互支持的群体,这种群体进一步排除他人的参与,并最终在组织中形成了派系。在考察影响派系形成的因素时,本文选取了与工作环境相关的两个变量以及表达组织气氛的一个变量。曲线图展示了本文的实验结果:接近或超过个人极限资源量的工作量和越不平均的工作量分配状况越有可能提高派系形成的速度和数量,并可能导致派系的不断分裂;而太小的工作量与过于均等的工作分配可使个体交往倾向减弱而处于相对孤立状态。

学术社交网络信息传播特征与规律研究

分析学术社交网络信息传播的特征,构造了一个学术社交网络信息传播模型.然后,通过编程提取了学术社交网络——研究之门网站中的用户数据,构造一个用户关系网络数据集.根据对随机内容的传播情况统计,绘制出信息传播的趋势图,同时还计算了该网络中信息传播的概率,形成了信息在网络中的传播规律.

网络信息传播动力学研究

对网络传播机理建模是运用网络和实施控制的基础。针对Web信息传播系统特有的复杂性，借鉴社会物理学的基本思想，对网络状态进行了离散化定义，并根据单信息源传播与机械波类比特征的相似性，提出了一种网站传播影响强度模型，从微观层面模拟网民个体在瞬态时间点上与离散的网站个体交互时，网络传播系统各动力学因子对网民传播行为的动态影响力；在此基础上，采用蒙特卡罗法将该模型与基于Agent仿真模型的个体交互规则相结合，建立了Web信息传播仿真模型。模型的运行结果能很好与实证研究相互印证，为类似问题的建模提供了一种新的思路。

基于双层网络的学生用户通讯行为分析与建模

随着手机成为人们生活的必需品,手机用户通讯行为的研究越来越深入,但仍缺少将通讯行为与用户的真实社交亲密度相关联的研究。文中通过采集真实的学生用户通讯行为数据和用户与联系人的社交属性关系,应用复杂网络和行为动力学相关理论,以学生用户为节点、常用通讯行为为连边、社交亲密度为权重,建立了基于社交网络和通讯网络的叠加网络。结合学生用户群体特有的行为模式,深入分析了社交网络与通讯网络之间的联系,以及社交属性对通讯行为幂律分布的影响。在此基础上,针对学生群体的通讯行为特征,建立了星型网络拓扑结构下,基于亲密度的多用户交互通讯行为模型(Intimacy Interaction Model),此模型充分考虑了社交网络对通讯网络的影响,可与真实通讯数据进行较好的拟合。

具有自我学习机制的网络谣言传播与仿真研究

将社交网络中的个体设为健康者(S)、传播者(I)、反击者(C)和免疫者(R)4种状态,根据不同状态之间的转移机制建立了SICR谣言传播模型.针对"人云亦云"的社会从众心理,引入个体的自我学习机制,基于BA无标度网络仿真分析了自我学习机制以及初始传播者、天然反击者重要性对谣言传播行为的影响.结果显示:自我学习机制能够促进谣言传播;初始传播者越重要,谣言传播范围越广、速度越快;天然反击者的重要性越高,抑制谣言传播的效果越明显.

人际竞争情报研究基本方法——网络建模

依据社会网络分析方法和人际竞争情报研究主题,本文从人际竞争情报建模对象、人际竞争情报网络模型描述、人际竞争情报网络静态研究、人际竞争情报网络动态研究四个方面论述人际竞争情报网络建模方法。本文认为人际竞争情报建模对象原则应根据其主要研究内容和功能来确定,1-mode和2-mode是人际竞争情报网络主要的模态,人际竞争情报只有从静态网络结构特征和动态网络演化趋势两个角度出发才能全面解决人际竞争情报各项研究主题。网络建模是人际竞争情报研究基本方法,是人际竞争情报规划、分析、传播以及维护的重要指导性工具。

动态社会接触网络上的H1N1控制仿真研究

给出了一个动态社会接触网络生成算法,基于该算法可得到同时具有无标度和小世界特性的网络模型;在讨论H1N1病程发展模型及传播参数的基础上,运用该模型对疫情在隔离、随机免疫、目标免疫和熟识者免疫四种控制措施下的发展趋势开展了仿真研究。仿真结果表明,目标免疫在上述四种控制措施中效能最高。模型算法与仿真结果对于传染病的社会传播控制有一定的理论和实践意义。