Network Analysis Approach Research Articles

Community resilience to wildfires: A network analysis approach by utilizing human mobility data

Disasters have been a long-standing concern to societies at large. With growing attention being paid to resilient communities, such concern has been brought to the forefront of resilience studies. However, there is a wide variety of definitions with respect to resilience, and a precise definition has yet to emerge. Moreover, much work to date has often focused only on the immediate response to an event, thus investigating the resilience of an area over a prolonged period of time has remained largely unexplored. To overcome these issues, we propose a novel framework utilizing network analysis and concepts from disaster science (e.g., the resilience triangle) to quantify the long-term impacts of wildfires. Taking the Mendocino Complex and Camp wildfires - the largest and most deadly wildfires in California to date, respectively - as case studies, we capture the robustness and vulnerability of communities based on human mobility data from 2018 to 2019. The results show that demographic and socioeconomic characteristics alone only partially capture community resilience, however, by leveraging human mobility data and network analysis techniques, we can enhance our understanding of resilience over space and time, providing a new lens to study disasters and their long-term impacts on society.

A socioemotional network perspective on momentary experiences of family conflict in young adults.

Family conflict is an established predictor of psychopathology in youth. Traditional approaches focus on between-family differences in conflict. Daily fluctuations in conflict within families might also impact psychopathology, but more research is needed to understand how and why. Using 21 days of daily diary data and 6-times a day experience-sampling data (N = 77 participants; mean age = 21.18, SD = 1.75; 63 women, 14 men), we captured day-to-day and within-day fluctuations in family conflict, anger, anxiety, and sadness. Using multilevel models, we find that days of higher-than-usual anger are also days of higher-than-usual family conflict. Examining associations between family conflict and emotions within days, we find that moments of higher-than-usual anger predict higher-than-usual family conflict later in the day. We observe substantial between-family differences in these patterns with implications for psychopathology; youth showing the substantial interplay between family conflict and emotions across time had a more perseverative family conflict and greater trait anxiety. Overall, findings indicate the importance of increases in youth anger for experiences of family conflict during young adulthood and demonstrate how intensive repeated measures coupled with network analytic approaches can capture long-theorized notions of reciprocal processes in daily family life.

Anxious and depressive symptoms and health-related quality of life in a cohort of people who recently attempted suicide: A network analysis

BackgroundSuicide is an international health concern with immeasurable impact from the perspective of human and social suffering. Prior suicide attempts, anxious and depressive symptoms, and relatively lower health-related quality of life (HRQoL) are among the most replicated risk factors for suicide. Our goal was to visualize the distribution of these features and their interconnections with use of a network analysis approach in individuals who recently attempted suicide. MethodsIndividuals with a recent suicide attempt were recruited from nine University Hospitals across Spain as part of the SURVIVE cohort study. Anxious and depressive symptoms, and perceived HRQoL were included in the network analysis. Network structures were estimated with the EBICglasso model. Centrality measures and bridge symptoms connecting communities were explored. Subnetworks comparing younger and older individuals, and women and men were analyzed. ResultsA total of 1106 individuals with a recent suicide attempt were included. Depressed mood was the symptom with the greatest influence in the overall network, followed by anxiety symptoms such as feeling nervous, worrying, restless, and having difficulties to relax. Perceived general health was associated with increased suicidal ideation in the whole sample. Older people showed a specific connection between perceived general health and depressed mood. LimitationsThe cross-sectional design does not allow determination of established causality. ConclusionsDepressed mood was the core network's symptom and, therefore, an important target in the management and prevention of suicide. HRQoL had more influence on the network of older populations, in which it should be a primary focus.

Characterizing Food Policy Councils' Network Partnerships and COVID-19 Responses.

The COVID-19 pandemic pushed millions of Americans into food insecurity. Food policy councils (FPCs) across the country played a vital role in organizing coordinated food responses across multiple sectors. We used a social network analysis (SNA) approach to investigate: (1) the network of partnering organizations and agencies within FPCs; (2) how the characteristics of FPCs' network partnerships (i.e., degree, coreness, and density) related to programmatic, policy, and advocacy actions in response to the pandemic; and (3) how FPCs' use of a racial or social equity framework shifted their network partnerships and responses. Local government agencies and food supply chain actors were core in FPCs' network partnerships, while public utilities, correctional facilities, social justice groups, and others were non-core partners. Network density was more likely to be associated with any action by FPCs, and it was especially pronounced for advocacy actions taken by FPCs; trends were similar among FPCs that reported using a racial or social equity framework. The findings begin to uncover core actors in FPCs' partnerships and opportunities to establish new partnerships, particularly with social justice groups. The results also suggest that network density (interconnectedness) may be more important than other network characteristics when responding to food-related needs.

Assessing botanical compatibility in gin production: A mathematical model and network analysis approach

This study introduces a novel methodology for evaluating volatile-compound-based compatibility in 160 botanicals essential for gin production. It establishes a comprehensive botanical pairing system through network analysis, mathematical modeling, and indicator development. Key findings include the benefits of strategic botanical inclusions to recipes for compatibility improvement and a numerical compatibility assessment, revealing an average indicator of 1.78 across thirty validated gin recipes, with a significant threshold at 1.36 indicating superior compatibility. Additionally, two distinct indicators were formulated—one focusing on the percentage of shared compounds due to a specific botanical and another on the botanical’s representation in the recipe. A visual network analysis replaces the traditional aroma classification wheel, offering a comprehensive view of aromatic profiles. This research transforms gin formulation, supported by an extensive database and validated methods.

Network analysis of maternal parenting practices and adolescent mental health problems: a longitudinal study

BackgroundAn extensive literature has shown a strong connection between maternal parenting practices and adolescent mental health problems. However, it has been difficult for previous research to map a dynamic concurrent and prospective relationships within and between types of parenting practices and adolescent mental health problems. The present study addressed these issues using a network analysis approach and a longitudinal design.MethodsThis study involved 591 Chinese adolescents (249 males; mean age at T1 = 13.53) and their mothers (mean age at T1 = 39.71) at two time points (T1 and T2) with eighteen months apart. Mothers reported their parenting practices including warmth, monitoring, inductive reasoning, hostility, and harshness, while adolescents reported their mental health problems including anxiety, depression, aggression, and conduct problems. Network analysis was conducted for contemporaneous networks at T1 and T2 and temporal networks from T1 to T2.ResultsThe contemporaneous networks revealed the negative association between monitoring and conduct problems served as the main pathway through which parenting practices and adolescent mental health mutually influenced each other, and further, warmth was the most influential parenting practice on adolescent mental health. The temporal network revealed that maternal hostility exerted the most influence on adolescent mental health problems, whereas adolescents’ depression was most influenced by maternal parenting practices. Moreover, maternal hostility was most predicted by maternal harshness.ConclusionsThis study presents a novel perspective to gain a better understanding of the dynamics between and within maternal parenting practices and adolescent mental health problems. Findings highlight maternal harshness and warmth as potential prevention and intervention targets for adolescent mental health problems.

Trust development in online competitive game environments: a network analysis approach

Trust seems to become established even in scenarios where the prerequisites for trust are complicated by conditions that evoke scepticism. Nonetheless, trust emerges, a phenomenon that is to be comprehended and examined in the present experimental inquiry. In order to comprehensively capture the process, a competitive online game environment was used to document the development of trust networks, directionality, and strength using network analysis. Despite the conditions conducive to distrust in this game setting, acts of trust were exhibited.Robust trust bonds persisting over the course of gameplay appear to manifest mostly dyadic or triadic, with participant embeddedness within the network and homophily in terms of general trustfulness towards strangers being conducive factors for trust bonding and game survivability. This study hence contributes to the overall understanding of online trust development and offers several further research opportunities in a mostly unexplored field.

I don’t want to switch! So, am I trapped? An in-depth qualitative inquiry of resistance to change leading to competency trap

PurposeThis paper explores the evident issue of organizational resistance to change. The study delves deep into the underlying resistance factors in organizations using a qualitative approach.Design/methodology/approachThe qualitative study employs a grounded theory coding pattern and network analysis to explore the underlying themes. This approach gives a panoramic view of resistance to change by comprehending the themes of existing literature and verbatims collected from the respondents.FindingsThe results of the comprehensive interviews and analyses suggest a significant change in the definition of resistance to change. The network analysis led to the identification of subthemes, antecedents, and consequences of resistance to change. The study highlights the importance of innovation, personnel training, mistrust, and the role of motivation.Practical implicationsThe insights gained from this practitioner-oriented study help navigate organizations to identify the issues related to resistance to change. The study also helps trace the issue of over-specialization, which promotes competency traps in organizations. The role of leaders in managing resistance to change is evident, which practitioners can consider for the more significant benefit of organizations.Originality/valueThe study proposes a nuanced understanding of resistance to change by using a qualitative approach to comprehend the phenomena from the perspective of leaders and employees. Using a coding approach for theme generation and network analysis for visualization ascertains the methodical rigor and comprehensive understanding alongside generating practitioner-oriented recommendations.

Interpersonal relationships and suicidal ideation among Chinese youths: A network analysis

BackgroundSuicidal ideation is a noteworthy health problem that requires further study in the field of interpersonal relationships. The main scope of relationships include family, teachers, peers, and the Internet. However, few studies have considered the effects of interpersonal interactions. Based on the Interpersonal Theory of Suicide, this study explores the relation between different interpersonal relationships and suicidal ideation. MethodsA network analysis approach was used to test the relationships. Cross-sectional data (N = 1694; 52.1 % boys; Mage = 11.86 years, SD = 1.59) were collected from primary and secondary students in October–November 2022. Participants completed a survey including demographic part and questionnaires: Positive and Negative Suicide Ideation Inventory (PANSI), Interpersonal Needs Questionnaire (INQ), Family Adaptability and Cohesion Evaluation Scale (FACES II), Inventory of Parent and Peer Attachment (IPPA), Student-Teacher Relationship Scale (STRS) and Facebook Intensity Scale (FIS). ResultsAll variables showed a significant correlation in this inferred network. Family, teacher-student, and peer relationships are protective against suicidal ideation. The closeness of the teacher-student relationship showed the highest strength centrality. However, online interpersonal relationship is a risk factor for suicide. Thwarted belongingness and perceived burdensomeness are proximal factors of suicidal ideation that influenced all interpersonal relationships. LimitationsThe network analysis as a data-driven and exploratory method may be limited to provide exact cause and effect relationship. ConclusionsThis study shows that teacher-student connections may be more important than other relationships of young people. Improper peer and online interpersonal relationship could be risky for suicide. Further studies are needed to examine the role of these relationships elaborately.

The Chronic Effects of a Single Low-Intensity Blast Exposure on Phosphoproteome Networks and Cognitive Function Influenced by Mutant Tau Overexpression.

Blast-induced neurotrauma (BINT) is a pressing concern for veterans and civilians exposed to explosive devices. Affected personnel may have increased risk for long-term cognitive decline and developing tauopathies including Alzheimer's disease-related disorders (ADRD) or frontal-temporal dementia (FTD). The goal of this study was to identify the effect of BINT on molecular networks and their modulation by mutant tau in transgenic (Tg) mice overexpressing the human tau P301L mutation (rTg4510) linked to FTD or non-carriers. The primary focus was on the phosphoproteome because of the prominent role of hyperphosphorylation in neurological disorders. Discrimination learning was assessed following injury in the subsequent 6 weeks, using the automated home-cage monitoring CognitionWall platform. At 40 days post injury, label-free phosphoproteomics was used to evaluate molecular networks in the frontal cortex of mice. Utilizing a weighted peptide co-expression network analysis (WpCNA) approach, we identified phosphopeptide networks tied to associative learning and mossy-fiber pathways and those which predicted learning outcomes. Phosphorylation levels in these networks were inversely related to learning and linked to synaptic dysfunction, cognitive decline, and dementia including Atp6v1a and Itsn1. Low-intensity blast (LIB) selectively increased pSer262tau in rTg4510, a site implicated in initiating tauopathy. Additionally, individual and group level analyses identified the Arhgap33 phosphopeptide as an indicator of BINT-induced cognitive impairment predominantly in rTg4510 mice. This study unveils novel interactions between ADRD genetic susceptibility, BINT, and cognitive decline, thus identifying dysregulated pathways as targets in potential precision-medicine focused therapeutics to alleviate the disease burden among those affected by BINT.

The Impact of Leadership on School Organizations: Network Analysis Approach to Systematic Review of Literature on Teaching and Learning International Survey

The purpose of this study is to review the literature on the Teaching and Learning International Survey (TALIS) for the past 10 years to identify multiple paths through which school leadership exerted influences on school organizations and organizational outcomes. Our analysis of a network, consisting of 83 nodes (variables) and 242 variable ties from 29 reviewed studies identified four emergent themes. Reviewed studies (1) overwhelmingly framed the principal as the driver and teachers as the target of change; (2) suggested nine core variables (e.g., instructional leadership) to play central roles within the reviewed studies; (3) depicted student academic achievement as a function of the principal’s instructional leadership and their job satisfaction influenced by school context, principal qualification, and organizational conditions (e.g., respect for others); and (4) suggested teacher self-efficacy as the potential bridging variable between multiple change processes. The discussion includes implications for school leadership and future research.

Supplemental Material for Identifying Candidate Mechanisms of Comorbidity in Disordered Eating and Posttraumatic Stress Disorder Symptoms Among U.S. Veterans: A Network Analytic Approach

Supplemental Material for Identifying Candidate Mechanisms of Comorbidity in Disordered Eating and Posttraumatic Stress Disorder Symptoms Among U.S. Veterans: A Network Analytic Approach

Influential upregulation of KCNE4: Propelling cancer associated fibroblasts-driven colorectal cancer progression

BackgroundColorectal cancer (CRC) is a malignancy of remarkable heterogeneity and heightened morbidity. Cancer associated fibroblasts (CAFs) are abundant in CRC tissues and are essential for CRC growth. Here, we aimed to develop a CAF-related classifier for predicting the prognosis of CRC and identify critical pro-tumorigenic genes in CAFs.MethodThe mRNA expression and clinical information of CRC samples were sourced from two comprehensive databases, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using a weighted gene co-expression network analysis (WGCNA) approach, CAF-related genes were identified and a CAF risk signature was developed through the application of univariate analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model. EdU cell proliferation assay, and transwell assay were performed to detect the oncogenic role of KCNE4 in CAFs.ResultsWe constructed a prognostic CAF model consisting of two genes (SFRP2 and KCNE4). CRC patients were classified into low- and high-CAF-risk groups using the median CAF risk score, and patients in the high-CAF-risk group had worse prognosis. Meanwhile, a higher risk score for CAFs was associated with greater stromal and CAF infiltrations, as well as higher expression of CAF markers. Furthermore, TIDE analysis indicated that patients with a high CAF risk score are less responsive to immunotherapy. Our further experiments had confirmed the strong correlation between KCNE4 and the malignant phenotypes of CAFs. Moreover, we had shown that KCNE4 could actively promote tumor-promoting phenotypes in CAFs, indicating its critical role in cancer progression.ConclusionThe two-gene prognostic CAF signature was constructed and could be reliable for predicting prognosis for CRC patients. Moreover, KCNE4 may be a promising strategy for the development of novel anti-cancer therapeutics specifically directed against CAFs.

Mining phase separation-related diagnostic biomarkers for endometriosis through WGCNA and multiple machine learning techniques: a retrospective and nomogram study.

The objective of this study was to investigate the role of phase separation-related genes in the development of endometriosis (EMs) and to identify potential characteristic genes associated with the condition. We used GEO database data, including 74 non-endometriosis and 74 varying-degree EMs patients. Our approach involved identifying significant gene modules, exploring gene intersections, identifying core genes, and screening for potential EMs biomarkers using weighted gene co-expression network analysis (WGCNA) and various machine learning approaches. We also performed gene set enrichment analysis (GSEA) to understand relevant pathways. This comprehensive approach helps investigate EMs genetics and potential biomarkers. Nine genes were identified at the intersection, suggesting their involvement in EMs. GSEA linked DEGs to pathways like complement and coagulation cascades, DNA replication, chemokines, apical plasma membrane processes, and diseases such as Hepatitis B, Human T-cell leukemia virus 1 infection, and COVID-19. Five feature genes (FOS, CFD, CCNA1, CA4, CST1) were selected by machine learning for an effective EMs diagnostic nomogram. GSEA indicated their roles in mismatch repair, cell cycle regulation, complement and coagulation cascades, and IL-17 inflammation. Notable differences in immune cell proportions (CD4 T cells, CD8 T cells, DCs, macrophages) were observed between normal and disease groups, suggesting immune involvement. This study suggests the potential involvement of phase separation-related genes in the pathogenesis of endometriosis (EMs) and identifies promising biomarkers for diagnosis. These findings have implications for further research and the development of new therapeutic strategies for EMs.

Social structures of urban governance: strategic spatial planning in Addis Ababa

ABSTRACT Focusing on strategic planning for spatial development, this paper explores the social structures that underpin urban governance in Addis Ababa, Ethiopia. To bridge the divide in the literature between studies that are narrowly focused on public service networks (typically more quantitative) and broader studies of urban governance (typically more qualitative), we use a social network analysis approach based on structured interviews to chart the actors and connections that influence the strategic planning process. Our results show that the governance network in this city is very homogeneous and centralised. The majority of actors at the core of strategic decision-making are city government entities, where most ties are structured around the Addis Ababa City Plan Commission and the mayor. With few exceptions (notably, the prime minister), other tiers of government, civil society organisations, the private sector and international donors are mostly peripheral. The fact that some powerful actors – such as international investors and the ruling coalition parties – are also playing a marginal role in the network may threaten governance stability and coherence. Although the mayor is a very powerful actor at the city level, the structural features of the governance network and the institutional power of the prime minister allow them to streamline their influence over the city’s future. The current governance regime for strategic spatial planning in Addis Ababa seems to privilege the effectiveness of the developmental agenda over the inclusiveness of the governing process. This has troubling implications for participatory development and the emergence of a more democratic society.

Building a communication and support network among quality improvement teams in nursing homes: a longitudinal study of the SCOPE trial

BackgroundWe applied a longitudinal network analysis approach to assess the formation of knowledge sharing and collaboration networks among care aide-led quality improvement (QI) teams in Canadian nursing homes participating in the Safer Care for Older Persons (in residential) Environments (SCOPE) trial which aimed to support unregulated front-line staff to lead unit-based quality improvement (QI) teams in nursing homes. We hypothesized that SCOPE's communicative and participatory nature would provide opportunities for peer support, knowledge sharing, and collaboration building among teams.MethodsFourteen QI teams in Alberta (AB) and seventeen QI teams in British Columbia (BC) participated in the study. Communications across nursing homes occurred through a series of 4 collaborative Learning Congresses (training sessions) over a 1-year period. The senior leaders of QI teams participated in two online network surveys about the communication/collaboration between teams in their province, 1 month after the first, and 6 months later, after the fourth Learning Congress. We developed communication and collaboration network maps pertaining to three time points: before SCOPE, at 2 months, and at 9 months.ResultsOver time, teams made significantly more new connections and strengthened existing ones, within and across regions. Geographic proximity and co-membership in organizational chains were important predictors of connectivity before and during SCOPE. Teams whose members were well connected at baseline disproportionately improved connectivity over time. On the other hand, teams that did not have prior opportunities to connect appeared to use SCOPE to build new ties.ConclusionsOur findings suggest the importance of network-altering activities to the formation of collaboration networks among QI teams across nursing homes. Active strategies could be used to better connect less connected teams and facilitate collaboration among geographically proximate teams. These findings may inform the development of interventions to leverage existing networks and provide new networking opportunities to develop and sustain organizational improvements.

Emergent leadership in agile software development teams: leader identification through network analysis and aggregation approaches

PurposeAgile project teams are self-managing and self-organizing teams, and these two characteristics are pivotal attributes of emergent leadership. Emergent leadership is thus common in agile teams – however, how these (informal) emergent leaders can be identified in teams remains far from understood. The purpose of this research is to uncover techniques that enable top management to identify emergent agile leaders.Methodology/designWe approached six agile teams from four organizations. We employ social network analysis (SNA) and aggregation approaches to identify emergent agile leaders.Design/methodology/approachWe approached six agile teams from four organizations. We employ SNA and aggregation approaches to identify emergent agile leaders.FindingsSeven emergent leaders are identified using the SNA and aggregation approaches. The same leaders are also identified using the KeyPlayer algorithms. One emergent leader is identified from each of the five teams, for a total of five emergent leaders from the five teams. However, two emergent leaders are identified for the remaining sixth team.Originality/valueEmergent leadership is a relatively new phenomenon where leaders emerge from within teams without having a formal leadership assigned role. A challenge remains as to how such leaders can be identified without any formal leadership status. We contribute by showing how network analysis and aggregation approaches are suitable for the identification of emergent leadership talent within teams. In addition, we help advance leadership research by describing the network behaviors of emergent leaders and offering a way forward to identify more than one emergent leader in a team. We also show some limitations of the approaches used and offer some useful insights.

Global change alters coastal plankton food webs by promoting the microbial loop: An inverse modelling and network analysis approach on a mesocosm experiment

Marine organisms are currently, and will continue to be, exposed to the simultaneous effects of multiple environmental changes. Plankton organisms form the base of pelagic marine food webs and are particularly sensitive to ecosystem changes. Thus, warming, acidification, and changes in dissolved nutrient concentrations have the potential to alter these assemblages, with consequences for the entire ecosystem. Despite the growing number of studies addressing the potential influence of multiple drivers on plankton, global change may also cause less obvious alterations to the networks of interactions among species. Using inverse analyses applied to data collected during a mesocosm experiment, we aimed to compare the ecological functioning of coastal plankton assemblages and the interactions within their food web under different global change scenarios. The experimental treatments were based on the RCP 6.0 and 8.5 scenarios developed by the IPCC, which were extended (ERCP) to integrate the future predicted changes in coastal water nutrient concentrations. Overall, we identified that the functioning of the plankton food web was rather similar in the Ambient and ERCP 6.0 scenarios, but substantially altered in the ERCP 8.5 scenario. Using food web modelling and ecological network analysis, we identified that global change strengthens the microbial loop, with a decrease of energy transfer efficiency to higher trophic levels. Microzooplankton responded as well by an increased degree of herbivory in their diet and represented, compared to mesozooplankton, by far the main top-down pressure on primary producers. We also observed that the organisation of the food web and its capacity to recycle carbon was higher under the ERCP 8.5 scenario, but flow diversity and carbon path length were significantly reduced, illustrating an increased food web stability at the expense of diversity. Here, we provide evidence that if global change goes beyond the ERCP 6.0 scenario, coastal ecosystem functioning will be subjected to dramatic changes.

Spatiotemporal analysis of global grain trade multilayer networks considering topological clustering

AbstractWith accelerating globalization, the complexity of the global grain trade network structure is increasing. Traditional network analysis approaches have certain limitations in capturing these dynamic changes and hidden topological structures in data. Based on global import and export trade data for rice, wheat, and corn from 1988 to 2022, this study has proposed a novel method for the topological clustering of temporal multilayer networks based on topological data analysis in order to systematically assess the topological structure evolution of temporal multilayer networks. The results indicate that different agricultural trade networks reveal hidden clustering characteristics in different years. In addition, this study combines principles from landscape ecology to construct a dynamic community spatiotemporal change model of grain trade networks, aiming to comprehensively reveal potential patterns and dynamic trends in grain trade networks and provide valuable information for grain trade decision‐making.

Dissemination of RT and Sputnik Content in European Digital Alternative News Environments: Mapping the Influence of Russian State-Backed Media Across Platforms, Topics, and Ideology

The study investigates the dissemination of news content from two Russian state-backed media outlets, RT and Sputnik, within digital alternative news environments in Austria, Denmark, Germany, and Sweden. We investigate these media outlets as parts of a Russian “sharp power” strategy, aimed at establishing informational influence within Western news environments. The analysis includes over 3.4 million social media posts containing URLs to RT and Sputnik content, published between January 2019 and March 2022. Drawing on a combined network analytical and computational text analysis approach, we examine the dissemination of RT and Sputnik content across a range of social media platforms (Twitter/X, Facebook, Telegram, VKontakte, Gab, Instagram, Reddit, 4chan, and YouTube). In the Danish and Swedish environments, the dissemination of content into core domestic alternative news communities is limited, primarily taking place on Facebook and, to a lesser extent, on Twitter/X. Fringe platforms such as Telegram, Gab and VKontakte facilitate a wider spread of content within domestic alternative news environments in German-speaking environments, predominantly among right-wing digital clusters. Within German-speaking alternative news environments, the shared content from RT and Sputnik primarily addresses domestic issues, such as COVID-19 policies and vaccines. In contrast, Danish- and Swedish-speaking alternative news environments emphasize foreign policy matters, including the Russian–Ukraine War, WikiLeaks, and Western military actions. These findings contribute to research on foreign state-media operations in digital information environments by focusing on both content and sharing patterns.