Social Network Analysis Research Articles

The cycle of violence: effects of violence experience, behavior, and attitudes on adolescents’ peer rejection networks

Previous research on adolescent peer networks has mainly focused on friendship networks and their association with violence, but very limited research is available on peer rejection networks. This lack of knowledge hinders the effectiveness of preventing peer rejection and its negative effects. Based on the theory of the cycle of violence, the present study examines the extent to which parental physical abuse experiences, aggressive behavior toward peers and acceptance of violence are related to peer rejection networks at school. Social network analysis with a stochastic actor-oriented model of longitudinal data collected from high school students (Wave 1, n = 620; Wave 2, n = 590) confirms that adolescents who frequently use aggression toward their peers are more likely to be rejected, especially if those adolescents have experienced abuse. Similarly, peers are more likely to reject adolescents with high levels of accepting violence. The results also show that aggression toward peers generally tends to decrease over time but not for adolescents who reject a larger number of students. For students who reject many peers, aggression frequency increases. From the perspective of resilience theory, peer rejection, when combined with aggression toward peers and acceptance of violence, particularly in female adolescents, creates a significant risk factor for socio-emotional development. Therefore, tackling violence attitudes, experiences and behavior in the school environment and at home is crucial in overcoming the cycle of violence.

Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network.

Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally and identifies aspects of information processing in complex environments that remain to be investigated. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

IMNE: Maximizing influence through deep learning-based node embedding in social network

Influence Maximization (IM) is a critical problem in social network analysis and marketing. It involves identifying a subset of nodes in a social network whose activation or influence can lead to the maximal spread of information, ideas, or behaviors within the network. Although many approaches have been developed in the literature to deal with this problem, most of these approaches are ineffective in dealing with large-scale social networks due to free parameters and computational complexity. Embeddings are used to learn low-dimensional representations of nodes in a social network. These embeddings capture the structural and semantic information of nodes and their relationships within the network. By training deep learning models on graph-structured data, node embeddings can capture complex patterns and dependencies in social networks, enabling more effective downstream tasks such as IM. Accordingly, this paper proposes an efficient algorithm to address the IM problem in social networks using deep learning-based Node Embedding (IMNE), which includes shell decomposition, graph/node embedding, and search space reduction as well as the use of local structural features. Our approach combines the power of deep learning for representation learning with the rich structural information present in social networks to address the challenge of IM in complex and dynamic social networks. IMNE uses the Independent Cascade (IC) information diffusion model to determine the labels needed to train the model by calculating the influence of nodes. Experimental results on several real-world networks considering different performance metrics show that IMNE performs better compared to existing baseline and state-of-the-art methods.

Elite cohesion and resilience of the Russian regions: the case of Belgorod Oblast

ABSTRACT What accounts for the ability of regional elites to respond to the challenges posed by the Russian war against Ukraine? This study argues that elite cohesion elevates the ability of subnational elites to cope and adapt to crises. It employs social network analysis of a novel biographical data set of elites’ connections in Belgorod Oblast, the border region that has been severely affected by the war. The analysis reveals that the war has made a relatively minor impact on the structure of the elite network as it has retained its original characteristics. Furthermore, it shows that the outsider governor has not only managed to strengthen his own position among the elites but also to reinforce elite cohesion. By bringing together different elite groups, the governor has enhanced their ability to perform under substantial stress. These findings advance our understanding of the sources of resilience in personalist autocracies.

Clustering and Optimizing Methods for Sprints of Agile Development Projects

To address the challenges of sprint planning and sequential optimization in agile development projects, this paper presents a model for agile sprint clustering and optimization. Firstly, we build an activity similarity network and measure the tie strength between activities using social network analysis (SNA) and design structure matrix (DSM). Then, we build an “overlap-iteration” model to measure the interactions strength between activities. Based on thecoupling strength (i.e. the sum of tie strength and interaction strength) between activities, this paper uses a two-stage clustering method to cluster the process DSM to obtain agile sprints. Furthermore, we measure the rework probability and rework intensity between sprints from the rework probability and rework intensity between activities to build an agile sprint optimization method. Finally, an agile development project example is provided to illustrate the validity of the proposed models. The results demonstrate that our approach significantly reduces project duration, cost, and rework risk in agile development projects.

Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM

Analyzing the driving factors and mechanisms of urban carbon emission correlation networks can provide effective carbon reduction decision-making support for Shandong Province and other regions with similar industrial characteristics. Based on industrial carbon emission data from various cities in Shandong Province from 2013 to 2021, the spatial correlation network of carbon emission was established by using a modified gravity model. The characteristics of the network were explored by using the Social Network Analysis (SNA) method, and significant factors affecting the network were identified through Quadratic Assignment Procedure (QAP) correlation analysis and motif analysis. The driving mechanism of the carbon emission correlation network was analyzed by using Temporal Exponential Random Graph Models (TERGMs). The results show that: (1) The spatial correlation network of urban carbon emission in Shandong Province exhibits multi-threaded complex network correlations with a relatively stable structure, overcoming geographical distance limitations. (2) Qingdao, Jinan, and Rizhao have high degree centrality, betweenness centrality, and closeness centrality in the network, with Qingdao and Jinan being relatively central. (3) Shandong Province can be spatially clustered into four regions, each with distinct roles, displaying a certain “neighboring clustering” phenomenon. (4) Endogenous network structures such as Mutual, Ctriple, and Gwesp significantly impact the formation and evolution of the network, while Twopath does not show the expected impact; FDI can promote the generation of carbon emission reception relationships in the spatial correlation network; IR can promote the generation of carbon emission spillover relationships in the spatial correlation network; GS, differences in GDP, differences in EI, and similarities of IR can promote the generation of organic correlations within the network; on the temporal level, the spatial correlation network of urban carbon emission in Shandong Province has shown significant stability during the study period.

Effective Stakeholder Management for Inclusive Post-Flood Management: Sri Lanka as a Case Study

This study aimed to examine post-flood management, with a particular focus on enhancing the inclusivity of marginalised communities through stakeholder analysis. This study was based on an interpretivist mixed method approach, under which 30 semi-structured stakeholder interviews were conducted. Interest versus power versus actual engagement matrix, social network analysis, and thematic analysis techniques were employed under the stakeholder analysis tool to analyse the collected data. The findings highlight the lack of clearly defined responsibilities among key stakeholders. Marginalised communities and community-based organisations have a high level of interests but a low level of power in decision making, resulting in weak engagement and the exclusion of their perceptions. This lack of collaboration and coordination among stakeholders has made marginalised communities more vulnerable in post-flood situations, as their interests are not defended. The findings emphasise the importance of conducting stakeholder analysis in the decision-making process to enhance stakeholder engagement and interaction, as well as promote inclusivity of marginalised communities in the post-flood recovery efforts of the government. Finally, this study recommends developing strategies to improve collaboration among stakeholders, fostering inclusiveness and customising these strategies according to the different types of stakeholders identified through stakeholder analysis.

Beyond mixed embeddedness: Multilevel personal networks of migrant entrepreneurs in Naples and Manchester

AbstractThis article analyses immigrant entrepreneurship in different urban contexts and recognizes its significant impact on the economic and sociocultural development of cities. Immigrant entrepreneurs are often concentrated in neighbourhoods and promote diversified economic activities. The mixed embeddedness (ME) framework highlights the complex interplay of contextual, economic and institutional factors that shape immigrant entrepreneurship. As a source of social capital, entrepreneurial networks provide access to resources and opportunities. Despite all progress, the systematic analysis and quantification of embeddedness among immigrant entrepreneurs remains a challenge. This article aims to understand how different urban contexts shape various entrepreneurial strategies by quantifying forms of embeddedness. To pursue this goal, we examined the entrepreneurial strategies of Sri Lankans in Rione Sanità (Naples, Italy) and Pakistani entrepreneurs in Rusholme (Manchester, United Kingdom). By using social network analysis, this article reveals distinct forms of embeddedness and how the characteristics of urban contexts and groups simultaneously help define differences in entrepreneurial strategies.

The BTS ARMY on Twitter flocks together: How transnational fandom on social media build a viable system

The world’s largest transnational fandom community of the BTS (BangTan Sonyeondan) ARMY (Adorable Representative M.C. for Youth) is structured to achieve common goals and exert influence. To identify a mechanism that explains the organizational structure of transnational virtual communities, we empirically investigate how the global fandoms carry out autonomous activities and adapt to the environment without coercive governance despite their massive size and complexity. Using the techniques of social network analysis and viable system model, we found some structural differences between the online communities with a viable and non-viable structure. First, the BTS ARMY network is sustained by a systematic structure of key players who voluntarily play distinct roles. In contrast, the Arianator network is relatively unorganized and dispersed. Moreover, multi-fandom accounts can act as potential user acquisition roles. Finally, two different diffusion types, text-based information and image-based media, are carried by distinct roles of subsystems. As one of the first studies to empirically examine the viability of online transnational fandom from an organizational structure perspective, this paper provides practical implications for fandoms from three perspectives; (1) resource mobilization and sustainability, (2) influence of fandom dynamics, and (3) economic impact. The results suggest that fandoms taking strategic actions upon the viable structure on digital platforms could represent a new cultural hegemony, promoting global unity and pop cosmopolitanism.

Research on urban agglomeration spatial network structure in the middle reaches of the Yangtze River based on real-time traffic accessibility scenario analysis

ABSTRACT Investigating the spatial network structure of urban agglomerations based on traffic accessibility has an important practical significance in accelerating the process of regional integration. Taking urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) as the case study, this study aims to examine the characteristics associated with the spatial network structure based on traffic accessibility and its changes under scenarios of different traffic accessibilities by adopting real-time traffic data, modified gravity model, and social network analysis (SNA). The main conclusions are as follows. Wuhan, Changsha, and Nanchang are the central cities in the spatial network; the spatial network structure of UAMRYR is imbalanced and in the agglomeration stage of regional economic development. With the development of traffic accessibility, resources first gather in the individual center cities and then spread to other cities, and the network tends toward equilibrium.

Typology of Terrorist Profiling Using Centrality Metrics: Hinge Figures, Influential Operatives and Trusted Assets

ABSTRACT The increase in terrorist activity worldwide has prompted the development of research tools and methodologies to study the phenomenon of terrorism. Among them, social network analysis (SNA) has found its way into the security studies discipline, which, despite its still timid presence, has increasingly been proven to be a useful tool for detecting underlying structures and key actors. This article seeks to contribute to the body of knowledge on the uses of SNA in the study of covert networks by testing the usefulness of metrics such as betweenness, closeness, and eigenvector centrality in identifying terrorist roles and functions in the cells that were behind the major terrorist attacks orchestrated by the Islamic State’s external operations apparatus. The study ends with the proposal of a new typology of terrorist profiling according to the results obtained from centrality measures: hinge figures, influential operatives and trusted assets.

‘University matching’ in state-regulated Sino-Australian transnational higher education: a Bourdieusian social network analysis

ABSTRACT The past three decades have seen proliferating research on Transnational Higher Education (TNHE), mostly understood through a market-oriented lens as a means of institutional and individual investment in economic and status gains. Less understood is the interplay between the state and the market logic in TNHE. Large-scale research on the market-state-status coordinated effect on TNHE is absent. This study makes a contribution in this regard through a Bourdieusian social network analysis of 130 state-regulated TNHE partnerships between 64 Chinese and 28 Australian universities. Descriptive analysis shows the evolvement of state-regulated Sino-Australian TNHE ‘networks’ over time from 2003 to 2019. Inferential statistics shows a significant homophily effect in the TNHE partnerships between Chinese and Australian universities with high rankings and research income. These results allude to a strong influence from the Chinese state on Sino-Australian TNHE partnerships.

Quality in care homes: How wearable devices and social network analysis might help.

Social network analysis can support quality improvement in care homes but traditional approaches to social network analysis are not always feasible in care homes. Recalling contacts and movements in a home is difficult for residents and staff and documentary and other sources of individual contacts can be unreliable. Bluetooth enabled wearable devices are a potential means of generating reliable, trustworthy, social network data in care home communities. In this paper, we explore the empirical, theoretical and real-world potential and difficulties in using Bluetooth enabled wearables with residents and staff in care homes for quality improvement. We demonstrate, for the first time, that a relatively simple system built around the Internet of Things, Bluetooth enabled wearables for residents and staff and passive location devices (the CONTACT intervention) can capture social networks and data in homes, enabling social network analysis, measures, statistics and visualisations. Unexpected variations in social network measures and patterns are surfaced, alongside "uncomfortable" information concerning staff time spent with residents. We show how technology might also help identify those most in need of social contact in a home. The possibilities of technology-enabled social network analysis must be balanced against the implementation-related challenges associated with introducing innovations in complex social systems such as care homes. Behavioural challenges notwithstanding, we argue that armed with social network information, care home staff could better tailor, plan and evaluate the effects of quality improvement with the sub-communities that make up a care home community.

A network of designs: studying Early Lapita exchange networks in the Bismarck Archipelago, Papua New Guinea through Social Network Analysis

ABSTRACTThe application of Social Network Analysis to the study of archaeological networks has become increasingly common around the world, with a proven track record of processing large, complex, spatial and temporal archaeological datasets. This study builds upon previous network‐based analyses of interaction between communities of the Lapita Cultural Complex, with a specific focus on the Early Period (c.3300/3200–3100 calBP) in the Bismarck Archipelago, Papua New Guinea. Employing motif inventories from 13 Early Lapita Period assemblages, motif similarity and Centrality Analysis are undertaken, with the results compared to data from portable material culture, particularly obsidian and pottery, to further define the networks of interaction that linked communities during this period. We conclude that motif similarities and Centrality Analysis scores show good agreement with patterns of interactions established from the analysis of other types of portable material culture, which together support the existence of northern west to east and southern obsidian distribution networks, comprised of communities that employed unique types of interaction tailored towards their own cultural and societal circumstances and needs. Finally, we further conclude that these two networks may have arisen during the initial formation of the Lapita Cultural Complex, as populations established new social connections with other settler communities and incumbent populations across the region to survive in a new and foreign environment.

Leaders of Peer Groups in Chinese Early Adolescents: The Roles of Social, Academic, and Psychological Characteristics in Group Leadership.

Leadership in peer groups is an important issue in adolescent socioemotional development, yet it has received limited attention in research. This one-year longitudinal study examined peer group leadership and the roles of social, academic, and psychological characteristics in the dynamics of group leadership. Participants included 1061 Chinese students (initial mean age =11.17 years; SD = 6.98 months; 49.4% female). Data were collected from peer assessments, teacher ratings, and self-reports. The longitudinal social network analysis (SIENA) indicated that peer group leadership was fluid with leadership status evolving over time across groups in a hierarchical manner. Adolescents displaying higher social competence and aggression and lower shyness were more likely to become group leaders. Academic performance and loneliness were not significantly associated with the dynamics of peer group leadership. The results help understand peer group leadership and contributions of social behaviors to the attainment of leadership status in peer groups in early adolescence.

Knowledge Graph Analysis On English Wikipedia Pages Using A Deep Learning Algorithm

Analysis of social networks or online communities can be very difficult when working on large networks, as many measurements require expensive hardware. For example, identifying the community structure of a network is a very computationally expensive task. Embedded graph is a way to represent graphs with vectors, so that further analysis becomes easier. The purpose of this research is to analyze the knowledge graph from the wikipedia article data. This research aims to implement web scraping techniques on the wikipedia article search engine and display similar wikipedia pages and analyze them using a predetermined deep learning algorithm. Data collection in this research used scraping techniques to retrieve data from the unstructured wikipedia website and then processed it into structured data. The method used in this research is a standard cross-industry process for data mining by performing phases of data collection, data processing, proposed algorithms, testing and evaluation. The algorithm applied is deepwalk, kmeans, girvan newman. By doing this research, it is expected to provide knowledge about the deep learning approach for data representation of the wikipedia pages knowledge graph and can help users find similar wikipedia pages and enrich literacy on knowledge graph analysis.

National Park Service Internal Structures Toward Agency Resilience: A Mixed-Methods, Multi-Site, Mesoscale Investigation

Agencies focused on protected areas’ conservation and recreation require internal capacity-building to enhance their organizational resilience (the ability to adapt and persist). Yet, internal capacity-building is often underemphasized as agencies attend to external relationships. This omission can lessen an agency’s ability to adapt to emergent stressors and opportunities. Specifically, relationships within an agency’s groups (i.e., divisions)—the intra-organizational mesoscale between individuals and whole organizations—can increase an agency’s ability to efficiently build resilience-enhancing adaptive capacity. The U.S. National Park Service (NPS) adopted this mesoscale in their Urban Agenda goal of One NPS, or building resilience-enhancing, agency-wide internal relationships. We investigated intra-organizational relationships in this context, examining relationships within (i.e., bonds) and across (i.e., bridges) three NPS groups: parks (physical spaces), programs (community outreach), and offices (administrative functions). Pairing qualitative interviews with quantitative social network analysis in Detroit, Tucson, and Boston, we examined internal relationship prevalence, supports, and opportunities. The NPS has program and office presence in each of these three urban areas but different proximities to national park units, which are the typical face of the NPS. Across these urban areas, we found that the parks group exhibits more bonds (park-to-park relationships), the programs group exhibits more bridges (program-to-park or program-to-office), and the offices group exhibits a mixture of bonds and bridges. To further One NPS and organizational resilience, cultivating bridges among the three groups is key. This investigation may inform a more strategic focusing of an agency’s limited resources. We highlight five directions for protected area managers’ consideration toward this aim: build bridges locally among groups; consider group composition when identifying divisions (i.e., programs appear more heterogeneous or dissimilar from each other than do the park and office groups); reflect on parks’ centrality to NPS identity and relationships; seek organizational structures supportive of relationship development; and focus on the organizational mesoscale for resilience-enhancing adaptive capacity. These directions for strategic focusing of organizational resources are based in the longstanding work of the NPS but ultimately transcend this single agency, providing targeted guidance for protected area agencies in building internal capacity toward external, public-oriented goals.

Mapping science through editorial board interlocking: connections and distance between fields of knowledge and institutional affiliations

AbstractResearch is a global enterprise underpinned by the general belief that findings need to be true to be considered scientific. In the complex system of scientific validation, editorial boards (EBs) play a fundamental role in guiding journals’ review process, which has led many stakeholders of sciences to metaphorically picture them as the “gatekeepers of knowledge.” In an attempt to address the academic structure that governs sciences through editorial board interlocking (EBI, the cross-presence of EB members in different journals) and social network analysis, the aim of this study is threefold: first, to map the connection between fields of knowledge through EBI; second, to visualize and empirically test the distance between social and general sciences; and third, to uncover the institutional structure (i.e., universities) that governs these connections. Our findings, based on the dataset collected through the Open Editors initiative for the journals indexed in the JCR, revealed a substantial level of collaboration between all fields, as suggested by the connections between EBs. However, there is a statistically significant difference between the weight of the edges and the path lengths connecting the fields of natural sciences to the fields of social sciences (compared to the connections within), indicating the development of different research cultures and invisible colleges in these two research areas. The results also show that a central group of US institutions dominates most journal EBs, indirectly suggesting that US scientific norms and values still prevail in all fields of knowledge. Overall, our study suggests that scientific endeavor is highly networked through EBs.

Why do users continue to contribute to darknet Child Sexual Abuse Material forums? Examining social exchange, social capital, and social learning explanations using digital forensic artifacts

BackgroundThe darknet hosts an increasing number of hidden services dedicated to the distribution of child sexual abuse material (CSAM). Given that by contributing CSAM to the forum members subject themselves to criminal prosecution, questions regarding the motivation for members contributing to darknet CSAM forums arise. ObjectiveBuilding on insights gained from research into clearnet communities, here we examine the extent to which social incentives generated by the online CSAM community may explain members' posting behavior on darknet CSAM forums. Participants and settingWe analyze digital forensic artifacts on the online behavior of members of a darknet CSAM forum that was shut down by law enforcement agencies in July 2015. MethodsWe apply group-based trajectory modelling (GBTM), social network analysis, and mixed-effect survival models. ResultsApplying GBTM three posting trajectories can be distinguished. Social network analyses finds the reply network to be more centralized than predicted by chance. Mixed-effect survival models show positive associations between the length of members' first post and the time since members' first registration on the forum and subsequent posting. Contrarily, the number of replies received appears to mitigate subsequent posting. ConclusionsFindings show posting activity on the forum to be concentrated in a minority of forum members who show posting trajectories that are both frequent and persistent. Results further suggest persistence in posting is motivated by social identity and, to a lesser extent, differential association processes.

A cross-cultural comparison of island vacation experience: empirical evidence from the Maldives

ABSTRACT This study compares the characteristics of Chinese and Western island vacation experience. Social network analysis was performed with 30 Chinese travel notes and 30 English travel notes, respectively. The results include: (1) The density and centralization of the Chinese island vacation experience network are lower than those of their Western counterparts; (2) Natural resources, tourism services, and recreational activities are the key dimensions of Chinese and Western island vacation experience, and seven common core experience elements exist; (3) The combination of “seascape-wild animals and plants-people” is preferred by both Chinese and Western tourists. Differences, however, exist between the two groups.