群体性事件的社会抗争模型及其研究展望

群体性事件是部分群众与行政当局或强势社会集团的对抗性冲突,为一种典型的集群行为。介绍了群体性事件的社会抗争模型,通过相对剥夺、群体认同和集体效能来解释群体性事件的心理机制。阐述了相对剥夺中的个体相对剥夺和群体相对剥夺、认知成分和情感成分对群体性事件的影响、群体认同与群体性事件的关系和集体效能对群体性事件的影响,并对近年来的研究进展做了介绍。最后指出社会抗争模型需要对模型中各因素的相互关系进行界定,并将其他重要因素如群际情绪、政治信任等因素包含到模型中。     

面向复杂决策场景的认知图谱构建与分析

在复杂网络场景中有效地甄别不同类别事件的性质和影响、辅助个体和组织决策、避免决策偏误,是复杂社会系统管理的重要研究问题。本文基于海量网络用户的交互内容数据,对网络数据中隐含的个体认知信息进行深度分析和系统化建模,提出了面向复杂决策场景的认知图谱构建与分析方法,从而对公众情绪的演变和群体性事件的走向进行可靠的预测。在中国股市中的高估信息、低估信息和披露信息3种不同类型事件中进行实验验证,结果表明：本文提出的认知图谱构建与分析方法能够解析不同类型复杂场景中个体认知要素变化与事件时空演化态势的关联关系,并能够有效支撑公众情绪的演化和群体性事件的预测与分析。     

群体性突发事件化解机制的随机演化博弈模型

有效化解群体性突发事件是各级政府维护社会和谐稳定面临的重要任务之一。促使抗议群体产生分化进而部分成员接受处置方案成为有效化解事件的关键环节。本文基于Moran过程的随机演化博弈理论，分析了抗议群体选择"退出抗议"策略成为均衡解的成立条件，揭示了群体性突发事件的内生化解机制。研究发现，系统的随机性越小，冲突双方争夺的经济资源越小，政府补偿额和冲突成本越大，群体性突发事件中抗议群体退出抗议的固定概率越大，事态趋于平息。抗议群众规模存在着一个能够成功化解的临界值。比较随机性干扰占据主导地位的弱选择过程和排除了随机性因素的强选择过程，后者具有更小的临界抗议群众规模。本文研究为揭示群体性事件的化解机制提供了一种基于随机演化博弈的新理论解释。     

维权型群体性突发事件社会网络结构与策略的协同演化机制

本文从社会网络分析角度揭示群体性突发事件的演化机理,建立了维权型群体性突发事件社会网络结构与策略的协同演化模型。首先,考虑变化的参与者心智模型和博弈环境,建立了五阶段动态博弈模型,在此基础上根据事态发展三个阶段讨论社会网络结构与策略协同演化机制;然后,根据弱势群体的社会网络拓扑特征,建立了维权型群体性突发事件社会网络结构与策略的协同演化模型,得出理性主义、利他主义和机会主义三种社会网络的最低抗议人数。研究表明:利他主义社会网络的最低临界人数较少,机会主义社会网络中核心组织成员需要承担更大的抗议成本。最后,Netlogo社会网络仿真分析和某住宅小区锅炉房扩建冲突的案例分析,验证了理论分析结果。     

管理越位现象:医患群体性事件社会网络的稳定性与效率

医患冲突问题成为当前社会热点问题之一。医患群体性事件当事者的社会网络结构呈现出越级上访、参与者个体的异质性、存在转移支付和动态递减的连接成本等复杂特征。在经典的社会网络JW模型上考虑上述社会网络特征,构建了修正的RJW(Revised Jackson-Wolinsky Model)社会网络模型。运用穷举搜索法,研究了医患冲突社会网络结构的稳定性和效率。结合南平医闹事件的案例分析,研究结果表明,当直接连接成本和连接收益较低时,星形社会网络稳定且高效;随着连接收益的上升,同时满足稳定性和有效的社会网络结构呈现出多种间接连接形态。该社会网络连接模型揭示了突发事件应急管理中“越位”、“越权”现象的产生条件:其关键因素是连接收益和连接成本的权衡。     

网络群体性事件发生机理与应对策略研究——基于社会燃烧理论

随着互联网的不断发展,作为社会矛盾或社会利益冲突的一种反映形式的网络群体性事件也愈来愈频繁。从社会燃烧理论的视角,分析网络群体性事件发生的演化机理,从社会燃烧物质(社会矛盾)、社会助燃剂(社会舆论)、社会点火温度(突发性事件)三个方面,提出解决网络群体性事件的相应策略。     

复杂交互行为影响下的网络舆情演化分析

如今网民参与网络舆情的现象愈加普遍，但国内网络舆情治理体制不完善，网络舆情事件易造成严重的负面影响，研究网络舆情的重要性日渐显著。基于演化博弈研究复杂网络中的网络舆情能够反映网络舆情形成和演化的实际情况，可以为引导相关主体参与网络舆情的行为和控制网络舆情的演化提供科学依据。本文在网络舆情的复制动态模型中引入两个可以反映网民复杂交互行为的因素：创建新博弈连接的行为偏好以及维持博弈连接的时间长短，在此基础上构建网络舆情演化博弈模型。根据演化博弈均衡解，分析、解释个体复杂交互行为因素以及网民初始得益对网络舆情演化的影响并针对不同情境提出相应的舆情治理建议。研究表明在交互连接达到稳态时，网络舆情博弈的得益矩阵会发生改变，新的得益矩阵由原来得益矩阵中的元素乘以其相应的博弈连接类型的活跃连接占比而构成。本文定量地解释相关主体间复杂的交互行为，研究结果对网络舆情危机处理以及疏导，减少网络舆情事件对社会的危害等都有参考价值。     

网络群体性事件的研究

随着网络媒体的流行,逐渐解构了中国原有的政治生态.笔者选取网络群体性事件作为研究样本,对网络群体性事件的特性及围观群体的行为及心理进行归纳分析,总结其体现的一般规律性,并由此对网络群体性事件的生成原因、折射出的社会阶层图景进行反思.同时对其所产生的影响进行严肃、客观的评判,并提出相应的解决举措促使网络群体性事件在民主社会建设进程中发挥积极的监督作用,真正成为维护公平与正义的有力武器.     

外生变量和非正社会影响推动群体观点极化

观点动向是群体行为研究的重要方面．群体的整体观点在个体间互动并在系统外因素共同影响下演化为不同模式．依据社会认同理论,给出了具体的 3 种社会影响,并在 Hopfield网络模型中引入了三元组关系结构．模型仿真证实了群体外生变量的干涉和负社会影响是推动群体观点极化的主要因素,群体观点极化是社会影响和结构平衡共同作用的结果．从结构平衡理论角度出发揭示了网络全局稳定极化模式与局部结构平衡的关系．     

高校网络群体性事件预防机制与应对策略研究

近年来,随着互联网事业的快速发展,高校群体性事件已经不仅仅发生在现实世界中,以网络为载体的群体性事件接踵发生,而且形成了网络与现实交替影响、相互放大的特点,受到了社会多方面的密切关注。在网络群体性事件中,各种信息借助网络快速传播,对现实中的事件起到推波助澜作用,增加了处理难度。这些频繁发生的网络群体性事件给党和政府应对突发事件的能力提出了新的挑战,也给高校管理工作增加了新的难度。     

移情关系影响下的群体共识决策模型研究

群体成员之间的社会关系及其网络结构特征是影响群决策的重要因素。移情关系是客观存在于一些现实群决策问题中的一种社会关系，但目前考虑移情关系的群决策研究尚不多见。为拓展群决策模型的应用范围，面向移情网络环境提出一种群体共识决策方法，并揭示移情关系对群体共识决策的影响规律。首先，从偏好交互影响的角度出发，构建局部移情模型和全局移情模型，并由此确定移情关系影响下决策者偏好演化的结果。其次，利用个体偏好分解为内在偏好和移情偏好的结构特点，为群体共识达成过程设计一种有效的移情关系引导的反馈机制，该机制可以通过内在偏好层面的偏好调整实现个体偏好层面的共识收敛。最后，数值仿真分析表明：群体成员之间的移情关系提升了群体共识水平，而且全局移情关系比局部移情关系更有利于群体共识的达成；移情网络结构和群体规模是影响移情网络环境下群体共识达成的重要因素。相关决策模型和研究结论可为移情网络环境下的群体共识决策提供理论和方法支持。     

Breakout from Bollywood? The roles of social networks and regulation in the evolution of Indian film industry

This paper combines evolutionary perspectives with social network theory in order to explain the recent growth of a prolific and changing indigenous industry in an emergent economy, namely the Indian film industry in Mumbai, India, Bollywood. Using novel and original data, the paper argues that as the world's biggest commercial film cluster and a conspicuous growth phenomenon, Bollywood can be seen as a paradigmatic case for developing general insights into indigenous growth of industries in emerging economies. The paper demonstrates how the existence of a well-defined and geographically centered social network among producers, directors and other key roles in filmmaking in Mumbai influences the evolution of a ‘Bollywood model’ of filmmaking remarkably different from Hollywood's. The paper adds to social network perspectives in evolutionary theory by suggesting that, given certain social network structures, policy regulation and other environmental factors may be instrumental for industry evolution.     

Path to “Stardom” in Globally Distributed Hybrid Teams: An Examination of a Knowledge‐Centered Perspective using Social Network Analysis

Although distributed teams have been researched extensively in information systems and decision science disciplines, a review of the literature suggests that the dominant focus has been on understanding the factors affecting performance at the team level. There has however been an increasing recognition that specific individuals within such teams are often critical to the team's performance. Consequently, existing knowledge about such teams may be enhanced by examining the factors that affect the performance of individual team members. This study attempts to address this need by identifying individuals who emerge as “stars” in globally distributed teams involved in knowledge work such as information systems development (ISD). Specifically, the study takes a knowledge‐centered view in explaining which factors lead to “stardom” in such teams. Further, it adopts a social network approach consistent with the core principles of structural/relational analysis in developing and empirically validating the research model. Data from U.S.–Scandinavia self‐managed “hybrid” teams engaged in systems development were used to deductively test the proposed model. The overall study has several implications for group decision making: (i) the study focuses on stars within distributed teams, who play an important role in shaping group decision making, and emerge as a result of a negotiated/consensual decision making within egalitarian teams; (ii) an examination of emergent stars from the team members’ point of view reflects the collective acceptance and support dimension decision‐making contexts identified in prior literature; (iii) finally, the study suggests that the social network analysis technique using relational data can be a tool for a democratic decision‐making technique within groups.     

The topology of collective leadership

Over the past decade, there has been a surge of both theoretical and empirical research to explore the possibilities of shared leadership, a reorientation of leadership away from understanding the actions and interactions of “leaders” to understanding the emergent, informal, and dynamic “leadership” brought about by the members of the collective itself. Naturally, this focus on topology (or structural patterning) has prompted researchers to leverage the advancements in network analytic methodology to understand this paradigm of leadership. Despite the recognition of the unique advantage of studying collective leadership using network analysis, there has been a translational gap. The current paper aims to fill this gap, bridging the core ideas that epitomize collective leadership to the social network metrics and analytics needed to fully understand its antecedents and consequences.     

基于多智能体的城市群政府合作建模与仿真——嵌入并反馈于一个异构性社会网络

以社会网络视阈下的城市群政府合作过程中的多期进化博弈为例,通过概念模型、数学模型和计算机模型的完整建模过程,在微观主体互动层面建立一个考虑个体成本收益差异的非对称进化博弈系统(并同时考虑全体博弈互动和部分博弈互动的交互),在宏观社会结构层面建立一个实现节点之间连接概率定制化的异构性社会网络模型(且同时考虑全局信息交互和局部信息交互的更替),并通过多智能体系统(特别是交互意愿变量的引入)实现了微观互动(博弈行为)和宏观涌现(网络结构)之间的双向反馈和动态交互.在构建模拟系统的基础上,设计并运行了一系列的实验方案,对仿真模型及模拟结果进行信度检验,并结合多次模拟实验样本数据的统计分析,考察全局交互比例,局部连接概率等网络结构变量、合作收益、惩罚措施等博弈参数变量、以及决策个性等主体属性变量对城市群政府博弈形势与合作水平的动态影响,为促进城市群政府合作和区域一体化进程提供决策依据和政策参考,也是政治学与公共行政学科计算实验研究的一次创新尝试.     

Identifying Social Interactions Through Conditional Variance Restrictions

This paper proposes a new method for identifying social interactions using conditional variance restrictions. The method provides a consistent estimate of the social multiplier when social interactions take the “linear‐in‐means” form (Manski (1993)). When social interactions are not of the linear‐in‐means form, the estimator, under certain conditions, continues to form the basis of a consistent test of the no social interactions null with correct large sample size. The methods are illustrated using data from the Tennessee class size reduction experiment Project STAR. The application suggests that differences in peer group quality were an important source of individual‐level variation in the academic achievement of Project STAR kindergarten students.     

产业创新网络动态演进机制模拟与实例分析

产业创新网络是由产业内以创新为目的、相互独立又相互关联的企业以及企业间关系耦合而成的网络.产业创新网络的演进机制是其研究的关键内容,但这一领域的研究成果、特别是定量研究成果较少.文章基于社会网络理论,将产业创新网络描述为企业间以创新为目的的关系网络;企业节点及其相互关系构成产业创新网络结构,知识资本和社会资本是产业网络创新的基础,企业的进入与退出机制以及企业的行为决策影响产业创新网络的演进过程,基于此构建基于多智能体的仿真模型来分析产业创新网络的演进机制;中国基于TD-SCDMA标准的3G产业网络演进过程实例表明,该仿真模型能够有效反映产业创新网络演进的特点,仿真模拟是分析产业创新网络演进机制的有效方法.     

Influence of Social Identity on Negative Perceptions in Global Virtual Teams

The paper combines insights from social identity theory and organizational network theory to specify the conditions under which social capital can induce negative attitudes in global virtual teams. The structural configuration of social capital has crucial implications for the sociocognitive processes causing individuals to adopt negative attitudes to out-group members. The paper evaluates both the negative implications of structural configurations on out-group perceptions, which are important precursors to successful intergroup interaction in global virtual teams. We collected data from 160 actors across 40 global virtual teams embedded within three separate organizations. 34 social identity groups were detected and ties between and within the groups were investigated. Our analyses provide insights on the roles of social identity groupings and social capital as well as in-group brokerage and interactions on (negative) perceptions of other group members in global virtual teams.     

Exploring the Impact of Social Axioms on Firm Reputation: A Stakeholder Perspective

This study proposes a model of how deeply held beliefs, known as ‘social axioms, moderate the interaction between reputation, its causes and consequences with stakeholders. It contributes to the stakeholder relational field of reputation theory by explaining why the same organizational stimuli lead to different individual stakeholder responses. The study provides a shift in reputation research from organizational‐level stimuli as the root causes of stakeholder responses to exploring the interaction between individual beliefs and organizational stimuli in determining reputational consequences. Building on a conceptual model that incorporates product/service quality and social responsibility as key reputational dimensions, the authors test empirically for moderating influences, in the form of social axioms, between reputation‐related antecedents and consequences, using component‐based structural equation modelling (n = 204). In several model paths, significant differences are found between responses of individuals identified as either high or low on social cynicism, fate control and religiosity. The results suggest that stakeholder responses to reputation‐related stimuli can be systematically predicted as a function of the interactions between the deeply held beliefs of individuals and these stimuli. The authors offer recommendations on how strategic reputation management can be approached within and across stakeholder groups at a time when firms grapple with effective management of diverse stakeholder expectations.