Identifying High betweenness Centrality Vertices in Large Noisy Networks

2013 ◽  
Author(s):  
Vladimir Ufimtsev ◽  
Sanjukta Bhowmick
Keyword(s):  
Betweenness Centrality ◽  
High Betweenness ◽  
High Betweenness Centrality

scholarly journals Family Networks and Distributive Politics

2019 ◽  
Vol 18 (4) ◽  
pp. 1697-1725 ◽  
Author(s):  
Marcel Fafchamps ◽  
Julien Labonne
Keyword(s):  
Betweenness Centrality ◽  
Public Services ◽  
The Philippines ◽  
Political Support ◽  
Goods And Services ◽  
Elite Status ◽  
High Betweenness ◽  
Aggregate Loss ◽  
Using Data ◽  
High Betweenness Centrality

Abstract We study the distribution of public services by local politicians when political support spreads through social networks. We sketch a model showing that incumbents target goods and services to individuals who would lead to the largest aggregate loss of support if they stopped supporting the incumbent. Those individuals have high betweenness centrality. Using data on 3.6 million households from the Philippines, we show that households with high betweenness centrality receive a greater number of public services from their local government. This result is robust to the inclusion of controls for program eligibility, detailed measure of family wealth and elite status, family ties with politicians, and other measures of centrality.

scholarly journals International collaboration of Polish research entities in a territorial context

2020 ◽  
Vol 64 (7) ◽  
pp. 118-129
Author(s):  
Anna Sworowska-Baranowska
Keyword(s):  
Betweenness Centrality ◽  
Scientific Collaboration ◽  
Mining Institute ◽  
Network Density ◽  
Special Focus ◽  
Degree Centrality ◽  
Significant Activity ◽  
Cross Border ◽  
High Betweenness ◽  
High Betweenness Centrality

The aim of the article was to characterize the structure of scientific collaboration launched by Polish institutions in partnership with foreign entities in 2019 with a special focus on the territorial context. An analysis of the network generated on the basis of data from the POL-on system was made: weak components, the degree centrality and the betweenness centrality for each entity were identified, as well as significant connections in the network reduced to the level of countries and to voivodeships. A key entity in the network was indicated (the Central Mining Institute). Some foreign entities show high betweenness centrality in the considered network. At the level of relations between countries, the high network density and significant activity of institutions from Germany were observed, which in the future may hinder gaining advantages. Scientific collaboration of Polish institutions is carried out mainly with centres located in Europe, but it is generally not cross-border.

scholarly journals The correlations between Th1 and Th2 cytokines in human alveolar echinococcosis

2020 ◽  
Author(s):  
Xiao Ma ◽  
Xuefei Zhang ◽  
Jia Liu ◽  
Yufang Liu ◽  
Cunzhe Zhao ◽  
...  
Keyword(s):  
Betweenness Centrality ◽  
Alveolar Echinococcosis ◽  
Healthy Control Group ◽  
Control Group ◽  
Th2 Cytokines ◽  
High Betweenness ◽  
Th1 And Th2 Cytokines ◽  
Healthy Control ◽  
High Betweenness Centrality ◽  
Th1 And Th2

Abstract Background: Alveolar echinococcosis (AE) is a cosmopolitan zoonotic parasitic disease caused by Echinococcus multilocularis larval tapeworm infections in humans that severely impairs the health of affected patients. Methods: The expression levels of 20 cytokines associated with AE infection were measured by enzyme-linked immunosorbent assay, and the correlations between these cytokines were analysed in the R programming language. Results: Serum cytokine levels differed among individuals in both the AE patient and healthy control groups. Related studies have shown that different cytokines are associated with AE. Therefore, we investigated the correlations among the cytokines; these correlations were simple in the healthy control group butcomplex in the AE patient group. Th2 cytokines, such as interferon (IFN)-γ, interleukin (IL)-1β and monocyte chemoattractant protein (MCP)-1, had high betweenness centrality in AE patients, whereas Th1 cytokines, such as growth-regulated oncogene (GRO)-α, eotaxin and IL-5, had high betweenness centrality in the healthy control group. Conclusions: The altered correlations between Th1 and Th2 cytokines may be closely associated with AE progression.

scholarly journals Identifying high betweenness centrality nodes in large social networks

2012 ◽  
Vol 3 (4) ◽  
pp. 899-914 ◽  
Author(s):  
Nicolas Kourtellis ◽  
Tharaka Alahakoon ◽  
Ramanuja Simha ◽  
Adriana Iamnitchi ◽  
Rahul Tripathi
Keyword(s):  
Social Networks ◽  
Betweenness Centrality ◽  
High Betweenness ◽  
High Betweenness Centrality

scholarly journals Jaringan Komunikasi Pelaku Inovasi Agribisnis Kolam Ikan Air Deras di Kecamatan Caringin Kabupaten Bogor

2017 ◽  
Vol 15 (1) ◽  
Author(s):  
Imsar Gunawan ◽  
Ninuk Purnaningsih ◽  
Basita Ginting
Keyword(s):  
Communication Network ◽  
Interpersonal Communication ◽  
Communication Networks ◽  
Betweenness Centrality ◽  
Fish Culture ◽  
Running Water ◽  
Water Fish ◽  
High Betweenness ◽  
Survey Results ◽  
High Betweenness Centrality

Running water fish culture is one of the techniques in freshwater fish cultivation. This activity forms an agribusiness system and interactions from the individuals involved. These interactions form a communication network. This study aimed to provide a description of running water fish culture innovation, analyze the interpersonal communication networks in running water fish culture agribusiness, factors that influence the interpersonal communication networks, and analyze the factors that influence business sustainability. This research which used the census method was conducted in Caringin Subdistrict Bogor Regency. Survey results show that the communication network formed was of scattered personal networks. The outdegree centrality and indegree centrality values obtained were categorized as medium respectively. The closeness centrality value is also in the medium category. Whereas the betweenness centrality value for running water fish agribusiness participants is known to be the highest. Those individuals with high betweenness centrality values possess the ability to organize communication in their networks.

Compressive sensing of high betweenness centrality nodes in networks

2018 ◽  
Vol 497 ◽  
pp. 166-184 ◽  
Author(s):  
Hamidreza Mahyar ◽  
Rouzbeh Hasheminezhad ◽  
Elahe Ghalebi K. ◽  
Ali Nazemian ◽  
Radu Grosu ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Betweenness Centrality ◽  
High Betweenness ◽  
High Betweenness Centrality

Modeling Team Cognition in Emergency Response via Naturalistic Observation of Team Interactions

2018 ◽  
Vol 62 (1) ◽  
pp. 1801-1802 ◽  
Author(s):  
Jukrin Moon ◽  
Farzan Sasangohar ◽  
S. Camille Peres ◽  
Timothy J. Neville ◽  
Changwon Son
Keyword(s):  
Emergency Response ◽  
Ad Hoc ◽  
Cognitive System ◽  
Team Cognition ◽  
Critical Elements ◽  
The Status ◽  
High Betweenness ◽  
Interactionist Perspective ◽  
Context Specific ◽  
High Betweenness Centrality

Emergency responders work collectively as an ad hoc team to save lives and infrastructures at risk, despite their varying experience, knowledge, cultural backgrounds, and difficult working conditions with high-levels of uncertainty and timepressure. Cognition, in particular, has gained attention as a key construct to consider in collective response efforts in emergency management. Team cognition, however, has not been fully appreciated or adequately addressed in the field of emergency response (Bigley & Roberts, 2001). The interactionist perspective (or interactive team cognition) effectively captures team cognition in heterogeneous and dynamic teams prevalent in the real-world (Cooke & Gorman, 2009; Cooke, Gorman, Myers, & Duran, 2013). Although researchers in the emergency response discipline appreciate the value of viewing team cognition as interaction (Comfort, 2007; Bergeron & Cooren, 2012; Wolbers & Boersma, 2013), an associated empirical or interventional attempt using this perspective remains scarce. Tracing the scarcity of literature back to lack of context-specific theorizing efforts (Moon, Peres, & Sasangohar, 2017), an observation-based, theory-building approach is utilized here to address this gap. The naturalistic observational study presented here is an initial effort to explore team cognition for an incident management team (IMT) as an interactive system. An IMT is an ad hoc team of command-level responders. Interestingly, an IMT is a team of functional sub-teams or sections (i.e., Command, Planning, Operations, Logistics, and Finance/ Administration). Within each sub-team there is also a team of functional units. This naturalistic observational study was conducted at a high-fidelity simulator replicating a generic IMT facility, i.e., the emergency operations training center (EOTC), College Station, TX. Interactions were observed and coded in terms of who initiated the interaction and with whom, which technology was being used, and what was communicated and for what purpose. The purpose of this study is to develop a theoretical interactionist model of team cognition in emergency response, to inform future interventional attempts to improve team decision-making. To do so, this study views a Plans team as a cognitive system capable of managing information through interdependent, nonlinear, and dynamic interactive behaviors for perceiving (P), diagnosing (D), and adapting (A) to the changes in the status of critical elements (Adapted from Moon et al., 2017). The proposed P·D·A model posits the following three premises: (1) a Plans team is a cognitive system where its team cognition is interactions of team members to complete a cognitive task; (2) team cognition for each of the three sub-teams of a Plans team is tied to the context-specific cognitive tasks of perceiving (P), diagnosing (D), and adapting (A) to the changes in the status of critical elements; and (3) team cognition for a Plans team is manifested as nonlinear, interdependent, and dynamic interactions within and among P, D, and A of the three sub-teams of the Plans team. Preliminary results from a content analysis of transcribed and coded interactions suggest that an Info/Intel unit, a Situation unit, and a Section Chief unit can be hypothesized to be critical contributors of team cognition for a Plans team in terms of P, D, and A, respectively. These hypotheses can be represented with network centrality measures as follows: Hypothesis 1. An Info/Intel unit has high in-degree and out-degree centrality with non-Plans teams. Hypothesis 2. A Situation unit has high betweenness centrality within a Plans team. Hypothesis 3. A Section Chief unit has high in-degree and out-degree centrality within a Plans team, and high betweenness centrality between the Plans team and non-Plans teams. The proposed P·D·A model illustrates the benefits of viewing team cognition as interaction within and among a team of teams, for context-specific tasks of P, D, and A. Most importantly, the model effectively captures the nonlinear, interdependent, and dynamic nature of team cognition as interaction in a multiteam system, or MTS (Marks, DeChurch, Mathieu, Panzer, & Alonso, 2005; Bienefeld & Grote, 2014), embedded in complex socio-technical systems, STS (Vicente, 2002). As the information processing model views an individual as a cognitive system or a human information processing system (Wickens, 1992), the P·D·A model views a team as a cognitive system capable of managing information. The interactionist perspective on team cognition helps the P·D·A model to realize its potential to extend an individual cognition model to a team level. The interactionist perspective is “compatible with the view of human-machine system as a unitary system” (Cooke & Gorman, 2009, p. 28). In addition to the theoretical and practical implications, this study has methodological implications. Measuring interactive team cognition with network-based metrics (currently in progress) will open a new chapter. The need of incorporating a network perspective into team cognition in emergency response is in line with the literature (Wolbers & Boersma, 2013; Steigenberger, 2016). As a future work, the P·D·A model will be further developed with network and content analysis and validated through interviews with Subject Matter Experts (SMEs) involved in Hurricane Harvey.

scholarly journals Topography Impacts Topology: Anatomically Central Areas Exhibit a “High-Level Connector” Profile in the Human Cortex

2019 ◽  
Vol 30 (3) ◽  
pp. 1357-1365 ◽  
Author(s):  
Jiahe Zhang ◽  
Lianne H Scholtens ◽  
Yongbin Wei ◽  
Martijn P van den Heuvel ◽  
Lorena Chanes ◽  
...  
Keyword(s):  
Information Integration ◽  
Betweenness Centrality ◽  
Brain Network ◽  
Predictive Processing ◽  
Central Position ◽  
Degree Centrality ◽  
Z Score ◽  
Topological Features ◽  
High Betweenness ◽  
High Level

Abstract Degree centrality is a widely used measure in complex networks. Within the brain, degree relates to other topological features, with high-degree nodes (i.e., hubs) exhibiting high betweenness centrality, participation coefficient, and within-module z-score. However, increasing evidence from neuroanatomical and predictive processing literature suggests that topological properties of a brain network may also be impacted by topography, that is, anatomical (spatial) distribution. More specifically, cortical limbic areas (agranular and dysgranular cortices), which occupy an anatomically central position, have been proposed to be topologically central and well suited to initiate predictions in the cerebral cortex. We estimated anatomical centrality and showed that it positively correlated with betweenness centrality, participation coefficient, and communicability, analogously to degree. In contrast to degree, however, anatomical centrality negatively correlated with within-module z-score. Our data suggest that degree centrality and anatomical centrality reflect distinct contributions to cortical organization. Whereas degree would be more related to the amount of information integration performed by an area, anatomical centrality would be more related to an area’s position in the predictive hierarchy. Highly anatomically central areas may function as “high-level connectors,” integrating already highly integrated information across modules. These results are consistent with a high-level, domain-general limbic workspace, integrated by highly anatomically central cortical areas.

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