Social Networks最新文献

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Hierarchy, Tasks, Space: An analysis of tie formation in the Palermo Mafia 层级、任务、空间：对巴勒莫黑手党关系形成的分析

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-04-30 DOI: 10.1016/j.socnet.2025.04.002

Michele Battisti , Andrea Mario Lavezzi , Roberto Musotto

We apply social network analysis to study tie formation among a large group of members of the Sicilian Mafia, one of the oldest criminal organizations, operating in the province of Palermo. Data come from the police operation denoted “Perseo”, which led to the arrest of 99 individuals active in the period 2006–2008. Specifically, we focus on the effect of hierarchical structure, task specialization patterns, and geographical organization on the probability of tie formation by estimating dyadic regressions. We find: First, if both agents in a dyad are bosses, two effects of opposite sign are at work: a scale effect, that increases the probability, and a homophily effect, that decreases such probability. Second, organizational task homophily positively affects tie formation, while criminal task homophily does not. Third, the key geographical variable driving tie formation is joint membership to the same mandamento, which makes sheer geographical distance non-statistically significant. We corroborate our results with several robustness tests and discuss their implications for an understanding of criminal organizations, such as the Cosa Nostra.

我们应用社会网络分析来研究在巴勒莫省活动的最古老的犯罪组织之一西西里黑手党的一大群成员之间的关系形成。数据来自警方代号为“Perseo”的行动，该行动逮捕了99名在2006-2008年期间活跃的个人。具体地说，我们通过估计二元回归来关注层次结构、任务专业化模式和地理组织对关系形成概率的影响。我们发现：首先，如果二分体中的两个主体都是老板，则两个相反符号的效应在起作用：规模效应（增加概率）和同质效应（减少概率）。第二，组织任务同质性对关系形成有正向影响，而犯罪任务同质性对关系形成无正向影响。第三，驱动纽带形成的关键地理变量是同一命令的联合成员资格，这使得纯粹的地理距离不具有统计意义。我们用几个稳健性测试证实了我们的结果，并讨论了它们对理解犯罪组织（如Cosa Nostra）的影响。

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引用次数: 0

Identifying stages in the lifespan of dynamic groups 确定动态群体生命周期的各个阶段

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-03-18 DOI: 10.1016/j.socnet.2025.03.002

Raji Ghawi, Jürgen Pfeffer

Dynamic groups, characterized by their evolving memberships, present unique challenges in understanding group behavior and performance. Traditional models often overlook the fluidity of group composition, focusing instead on static memberships. In this paper, we introduce a comprehensive framework to empirically measure and analyze changes in group composition over time, offering new insights into group dynamics. We propose key metrics, including Growth Rate, Churn, and Revitalization, that quantify the movement of members in and out of groups. Further, we define distinct stages of group development, such as organic growth, dynamic growth, fluid stability, and erosion, which capture the evolving nature of group composition. A data-driven method is presented to systematically identify these stages across a group’s lifespan. As a case study, we apply our methodology to a dataset from the massively multiplayer online game Travian, involving nearly 900 alliances and over 17,000 players, revealing common patterns of group evolution and frequent transitions between growth and decline. Our findings underscore the value of understanding group stages, offering practical implications for managing dynamic groups in various organizational settings.

动态群体的特点是其成员不断演变，在理解群体行为和表现方面提出了独特的挑战。传统模型往往忽略了群体构成的流动性，而是关注静态成员。在本文中，我们引入了一个全面的框架来实证测量和分析群体组成随时间的变化，为群体动力学提供了新的见解。我们提出了关键指标，包括增长率，流失率和振兴，量化成员在群体内外的运动。此外，我们定义了群体发展的不同阶段，如有机生长、动态生长、流体稳定性和侵蚀，这些阶段捕捉了群体组成的演变本质。提出了一种数据驱动的方法来系统地识别群体生命周期中的这些阶段。作为一个案例研究，我们将我们的方法应用于大型多人在线游戏《Travian》的数据集，该数据集涉及近900个联盟和超过17,000名玩家，揭示了群体进化的共同模式以及在增长和衰退之间的频繁转换。我们的研究结果强调了理解群体阶段的价值，为在各种组织环境中管理动态群体提供了实际意义。

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引用次数: 0

Podcasts in the periphery: Tracing guest trajectories in political podcasts 外围播客：追踪政治播客中的嘉宾轨迹

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-03-27 DOI: 10.1016/j.socnet.2025.03.003

Sydney A. DeMets, Emma S. Spiro

Social networks structure the flow of political information that is critical for civic participation and individual decision making, simultaneously opening and constraining the diffusion of ideas and information. Understanding the current information landscape is pressing given the current salience of false and misleading information. Given the growing prominence of podcasts within the information ecosystem, and the high levels of trust that podcasters enjoy from listeners, it is critical to better understand the role this medium plays in political communication. In this paper, we construct a bipartite network of podcasts and their invited guests. We then generate a network of paths that guests take as they move from one podcast to the next using entailment analysis, and evaluate if guests are typically invited to speak on less prominent shows first, before moving on to more prominent shows. This dynamic has several parallels to Centola’s power of the periphery hypothesis, complimented by the idea that guests may visit progressively more prominent podcasts as they themselves become more visible. We also find that shows aiming to feature a politically diverse set of guests on their own shows play an outsize role in brokering the movement of guests between liberal and conservative shows, although this cross-boundary brokerage has equivocal outcomes.

社会网络构建了政治信息的流动，这对公民参与和个人决策至关重要，同时也开放和限制了思想和信息的传播。鉴于当前虚假和误导性信息的突出性，理解当前的信息景观是紧迫的。鉴于播客在信息生态系统中日益突出，以及听众对播客的高度信任，更好地理解这种媒介在政治传播中所起的作用至关重要。在本文中，我们构建了一个播客及其邀请嘉宾的二部网络。然后，我们使用蕴涵分析，生成一个嘉宾从一个播客转到下一个播客的路径网络，并评估嘉宾是否首先被邀请在不太突出的节目上发言，然后再转到更突出的节目上。这种动态与森托拉的外围假说的力量有几个相似之处，他补充说，随着客人们自己变得越来越显眼，他们可能会逐渐访问更著名的播客。我们还发现，旨在在自己的节目中展示政治多元化嘉宾的节目，在促成嘉宾在自由派和保守派节目之间的流动方面发挥了巨大的作用，尽管这种跨界中介的结果模棱两可。

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引用次数: 0

Investigating the dynamics of yakuza violence using multilevel network analysis 利用多层次网络分析调查黑帮暴力的动态

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-03-11 DOI: 10.1016/j.socnet.2025.03.001

Niles Breuer, Martina Baradel

This paper investigates the structure of the yakuza – the Japanese mafia – and the patterns of violence between local yakuza groups using a novel dataset of yakuza-on-yakuza conflict throughout Japan between 2014 and 2019. We define new multilevel temporal reciprocity measures and apply a multilevel exponential random graph model to investigate the structure of yakuza violence. We find low levels of retaliation and complex ‘cascading’ conflict structures and that yakuza syndicates act as cohesive organizations that can constrain the actions of their member groups. This research contributes to the understanding of the yakuza’s structure and how violent conflict occurs within organized crime groups.

本文利用2014年至2019年日本各地黑帮之间冲突的新数据集，研究了日本黑帮的结构以及当地黑帮之间的暴力模式。我们定义了新的多层时间互易测度，并应用多层指数随机图模型来研究黑帮暴力的结构。我们发现报复程度较低，复杂的“级联”冲突结构，而且黑帮集团是一个有凝聚力的组织，可以约束其成员团体的行动。这项研究有助于了解日本黑帮的结构以及有组织犯罪集团内部暴力冲突的发生方式。

引用次数: 0

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-04-10 DOI: 10.1016/j.socnet.2025.02.003

Maurice Bokanga, John Levi Martin

While many recent examinations of the idea of duality build upon it to quantify the similarity of entities in a data matrix, there is a potential avenue for quantifying the diversity of some ensemble, but this has not yet been given attention. We here draw on a robust line of work in mathematical ecology that has developed a family of entropy-related diversity measures, and we explore generalizing them to cases of dual nesting. Combining duality-based thinking with ecological diversity measures helps resolves some inherent ambiguities in the way that social scientists often think about diversity: the same relations that appear to increase diversity in some respects may, from a different perspective, decrease diversity. Such ambiguities can interfere with examining some of the most interesting theories of the effects of development on social life. We illustrate with network data from a sample of residents of 75 Indian villages, also cross-nested in 38 castes (jati).

虽然最近对对偶概念的许多研究都建立在它的基础上，以量化数据矩阵中实体的相似性，但有一种潜在的途径可以量化某些集合的多样性，但这一点尚未得到重视。我们在这里借鉴了数学生态学中一个强有力的工作路线，它已经开发了一系列与熵相关的多样性措施，我们探索将它们推广到双重嵌套的情况。将基于二元性的思维与生态多样性测量相结合，有助于解决社会科学家经常思考多样性的一些固有的模糊性：从不同的角度来看，在某些方面似乎增加了多样性的相同关系可能会减少多样性。这种模糊性可能会干扰对一些最有趣的关于发展对社会生活影响的理论的研究。我们用来自75个印度村庄的居民样本的网络数据来说明，这些村庄也交叉嵌套在38个种姓（贾提）中。

引用次数: 0

Deviations from cultural consensus about occupations: The duality of occupation meanings and Americans’ meaning communities 关于职业的文化共识的偏差：职业意义和美国人意义社区的双重性

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-04-18 DOI: 10.1016/j.socnet.2025.04.003

Aidan Combs , Gabriel Varela , Dawn T. Robinson , Lynn Smith-Lovin , Stephen Vaisey

We examine ratings of 642 occupations by a national online sample of U.S respondents in 2019 (Freeland et al., 2020). We analyze the respondents’ ratings of occupations on three dimensions of cultural meaning—evaluation (good versus bad), potency (powerful versus powerless), and activity (lively versus quiet). We take deviations of respondents’ individual ratings from population evaluation, potency and activity estimates, focusing on deviations from consensus rather than consensus itself. Drawing on Breiger's (1974) work on duality, we examine two projections of the initial rectangular matrix of correlated deviations. Our two projections represent (1) the cultural communities that people form when they differ from consensus in similar ways, and (2) the clusters of occupations that move in similar ways across those subcultures. Correlations among the residuals at the person level are indicators of shared subcultural differences from the mainstream—different ways of meaning-making about what is valuable and worthy about occupational work. At the occupation level, the structure represents schemas for which occupations share common elements and move together when those elements are evaluated differently. We use dyad models to investigate what metrics of occupation similarity predict similarity in deviations from consensus. We find that similarity in affective meaning (evaluation, potency and activity), material requirements, rewards, and work characteristics all predict clustering at the occupation level. Demographic composition of occupations is less important. We find that older respondents, White respondents, and higher income respondents tend to discriminate more between occupations on evaluation and potency. Respondents who are more similar in age have more similar patterns of deviations. However, occupation-level variables are in general much stronger predictors of residual structure than respondent-level variables.

我们研究了2019年美国受访者的全国在线样本对642个职业的评分（Freeland et al., 2020）。我们从文化意义评价（好与坏）、效力（强大与无能）和活动（活跃与安静）三个维度分析受访者对职业的评价。我们从人口评估、效力和活动估计中获取受访者个人评级的偏差，重点关注与共识的偏差，而不是共识本身。借鉴Breiger（1974）关于对偶性的工作，我们研究了相关偏差的初始矩形矩阵的两个投影。我们的两个预测代表了(1)当人们以相似的方式与共识不同时形成的文化社区，以及(2)在这些亚文化中以相似的方式移动的职业集群。在个人层面上，残差之间的相关性是来自主流的共同亚文化差异的指标——不同的意义创造方式，关于职业工作的价值和价值。在职业级别，该结构表示模式，其中职业共享公共元素，当这些元素的评估方式不同时，这些元素会一起移动。我们使用二元模型来研究职业相似度的指标预测一致性偏差的相似度。我们发现情感意义（评价、效力和活动）、物质要求、奖励和工作特征的相似性都预测了职业水平上的聚类。职业的人口构成不那么重要。我们发现，年龄较大的被调查者、白人被调查者和高收入的被调查者更倾向于在评估和效力上对职业进行歧视。年龄越相近的受访者，其偏差模式也越相似。然而，职业水平的变量通常比被调查者水平的变量更能预测剩余结构。

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引用次数: 0

From warnings to bans: The role of social networks in the severity of sanctions 从警告到禁令：社交网络在严厉制裁中的作用

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-07-01 Epub Date: 2025-02-14 DOI: 10.1016/j.socnet.2025.02.001

Mélina Girard, David Décary-Hétu

This study examines the influence of social networks on the severity of sanctions in an online hacking forum, using a leaked dataset containing private interactions, reputation points, and administrative actions. Applying social identity theory, power structure, and social capital concepts to social network analysis, we find that members who committed spam, lacked bidirectional relationships with admins, and were less integrated and influential were more likely to be banned than warned. Our findings highlight the significant role of social ties and individual behaviors in determining sanctions, offering new insights into the dynamics of illicit online communities.

本研究考察了社交网络对在线黑客论坛制裁严重程度的影响，使用了一个包含私人互动、声誉点和行政行为的泄露数据集。运用社会认同理论、权力结构和社会资本的概念对社会网络进行分析，我们发现那些滥发垃圾邮件、与管理员缺乏双向关系、整合程度和影响力较低的成员更容易被封禁而不是警告。我们的研究结果强调了社会关系和个人行为在决定制裁方面的重要作用，为非法在线社区的动态提供了新的见解。

引用次数: 0

Revising the Borgatti-Everett core-periphery model: Inter-categorical density blocks and partially connected cores 对Borgatti-Everett核心-外围模型的修正：分类间密度块和部分连通核心

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-05-01 Epub Date: 2024-12-16 DOI: 10.1016/j.socnet.2024.11.002

José Luis Estévez , Carl Nordlund

Borgatti and Everett's model (2000) remains the prevailing standard for identifying categorical core-periphery structures in empirical networks, yet this method poses two significant issues. The first concerns the handling of inter-categorical ties—those linking core and periphery actors. The second problem is the model's definition of the ideal core as a complete block or clique, which can be overly stringent in practical applications. Building on advancements in direct blockmodeling, we propose modifications to address these shortcomings. To better handle inter-categorical ties, we replace the traditional cell-wise correlation approach with one based on exact- and minimum-density blocks. To relax the constraint of a fully connected core, we introduce the p-core, a proportional adaptation of the k-core/k-plex cohesive subgroups, providing greater flexibility in defining the level of cohesion required for core membership. We illustrate the advantages of these enhancements using both classic network examples and synthetic networks.

Borgatti和Everett的模型（2000）仍然是识别经验网络中分类核心-外围结构的主流标准，但这种方法存在两个重大问题。第一个问题涉及处理类别间联系——那些连接核心和外围行为者的联系。第二个问题是该模型将理想核心定义为一个完整的区块或集团，这在实际应用中可能过于严格。基于直接块建模的进步，我们提出了一些修改来解决这些缺点。为了更好地处理分类间的联系，我们用基于精确和最小密度块的方法取代了传统的细胞相关方法。为了放松完全连接核心的约束，我们引入了p-核心，这是k-核心/k-plex内聚子群的比例适应，在定义核心成员所需的内聚水平方面提供了更大的灵活性。我们使用经典网络示例和合成网络来说明这些增强的优点。

引用次数: 0

Digital communication and tie formation amongst freshmen students during and after the pandemic 大流行期间和之后新生之间的数字通信和关系形成

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-05-01 Epub Date: 2025-01-10 DOI: 10.1016/j.socnet.2024.12.002

Judith Gilsbach , Johannes Stauder

This study examines the network evolution among sociology freshmen students during and after the Covid-19 pandemic as a natural experiment on the impacts of digitalised communication. The first surveyed cohort (N = 42) began their studies under lockdown in October 2020, when all classes were taught online (lockdown cohort). The second cohort (N = 66) started one year later when the lockdown measures were released partly and most classes were taught in a hybrid mode (hybrid cohort). We use Stochastic Actor-Oriented Models (SAOM) for model estimation; missing relations due to actor non-response are multiply imputed using SAOM-based procedures. The findings show (1) that the network among students of the lockdown cohort developed slower and reached a lower density at the end of the first term, (2) that the probability of triadic closure was significantly lower in the lockdown than in the hybrid cohort and (3) that in both cohorts, students have a stronger tendency to get acquainted if they share classes, but (4) that shared classes were more important for tie formation during lockdown. We conclude that digital communication will mitigate the opportunities to make new acquaintances and friends.

本研究考察了新冠疫情期间和之后社会学大一新生的网络演变，作为数字化传播影响的自然实验。第一个被调查的队列（N = 42）于2020年10月在封锁期间开始学习，当时所有课程都是在线授课（封锁队列）。第二批（N = 66）开始于一年后，当时封锁措施部分解除，大部分课程采用混合模式（混合队列）。我们使用随机因子导向模型（SAOM）进行模型估计；由于参与者不响应而导致的缺失关系使用基于saom的过程进行多重估算。研究结果表明：(1)封锁队列学生之间的网络发展速度较慢，在第一学期结束时密度较低；(2)封锁队列中三合一封闭的概率显著低于混合队列；(3)在两个队列中，如果学生共享班级，他们更倾向于认识，但(4)共享班级对封锁期间的关系形成更重要。我们的结论是，数字通信将减少结交新朋友和新朋友的机会。

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引用次数: 0

Estimating policy effects in a social network with independent set sampling 用独立集抽样估计社会网络中的策略效果

IF 2.9 2区社会学 Q1 ANTHROPOLOGY

Social Networks

Pub Date : 2025-05-01 Epub Date: 2024-11-28 DOI: 10.1016/j.socnet.2024.10.002

Eugene T.Y. Ang , Prasanta Bhattacharya , Andrew E.B. Lim

Evaluating the impact of policy interventions on respondents who are embedded in a social network is often challenging due to the presence of network interference within the treatment groups, as well as between treatment and non-treatment groups. In this paper, we propose a novel empirical strategy that combines network sampling based on the identification of independent sets with a stochastic actor-oriented model (SAOM) to infer the direct and net effects of a policy. By assigning respondents from an independent set to the treatment, we are able to block direct spillover of the treatment among the treated respondents for an extended period of time, during which the direct effect of the treatment can be isolated from the associated network interference. We empirically demonstrate this using a simulation-based evaluation of a fictitious policy implementation using both real-life and generated networks, and use a counterfactual approach to estimate the treatment effect of the policy. Our results highlight the effectiveness of our proposed empirical strategy, and notably, the role of network sampling techniques in influencing the evaluation of policy effects. The findings from this study have the potential to help researchers and policymakers with planning, designing, and anticipating policy responses in a networked society.

由于在治疗组内部以及治疗组和非治疗组之间存在网络干扰，评估政策干预对嵌入社会网络的受访者的影响往往具有挑战性。在本文中，我们提出了一种新的经验策略，将基于独立集识别的网络抽样与随机因素导向模型（SAOM）相结合，以推断政策的直接和净效应。通过将受访者从一个独立的集合分配到治疗中，我们能够在较长一段时间内阻止治疗在接受治疗的受访者之间的直接溢出，在此期间，治疗的直接效果可以与相关的网络干扰隔离开来。我们通过使用现实生活和生成的网络对虚拟政策实施进行基于模拟的评估，并使用反事实方法来估计政策的治疗效果，从而经验地证明了这一点。我们的结果突出了我们提出的实证策略的有效性，值得注意的是，网络抽样技术在影响政策效果评估中的作用。这项研究的发现有可能帮助研究人员和政策制定者在网络社会中规划、设计和预测政策反应。

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