The individual‐based network structure of palm‐seed dispersers is explained by a rainforest gradient

Oikos ◽  
2021 ◽  
Author(s):  
Pâmela Friedemann ◽  
Marina Corrêa Côrtes ◽  
Everaldo Rodrigo de Castro ◽  
Mauro Galetti ◽  
Pedro Jordano ◽  
...  
Keyword(s):  
Network Structure ◽  
Seed Dispersers ◽  
The Individual

scholarly journals The architecture of network collective intelligence : correlations between social network structure, spatial layout and prestige outcomes in an office

2018 ◽  
Vol 373 (1753) ◽  
pp. 20170238 ◽  
Author(s):  
Felichism Kabo
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Collective Intelligence ◽  
Physical Space ◽  
Spatial Layout ◽  
Spatial Proximity ◽  
Cross Sectional ◽  
Interdisciplinary Approaches ◽  
Level I ◽  
The Individual

A social network represents interactions and knowledge that transcend the intelligence of any of its individual members. In this study, I examine the correlations between this network collective intelligence , spatial layout, and prestige or status outcomes at the individual and team levels in an organization. I propose that spatially influenced social cognition shapes which individuals become members of prestigious teams in organizations, and the prestige perception of teams by others in the organization. Prestige is a pathway to social rank, influence and upward mobility for individuals in organizations. For groups, perceived prestige of work teams is related to how team members identify with the group and with their collaborative behaviours. Prestige enhances a team's survivability and its access to resources. At the individual level, I ran two-stage Heckman sample selection models to examine the correlation between social network position and the number of prestigious projects a person is a member of, contingent on the association between physical space and social ties and networks. At the team level, I used linear regressions to examine the relationship among network structure, spatial proximity and the perceived prestige or innovativeness of a project team. In line with my hypotheses, for individuals there is a significant correlation between physical space and social networks, and contingent on that, between social network positions and the number of prestigious projects that a person is a member of. Also in accordance with my hypotheses, for teams there is a significant correlation between network structure and spatial proximity, and perceived prestige. While cross-sectional, the study findings illustrate the importance of considering the spatial domain in examinations of how network collective intelligence is related to organizational outcomes at the individual and team levels. This article is part of the theme issue ‘Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour’.

scholarly journals Ego-zones: non-symmetric dependencies reveal network groups with large and dense overlaps

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Milos Kudelka ◽  
Eliska Ochodkova ◽  
Sarka Zehnalova ◽  
Jakub Plesnik
Keyword(s):  
Network Structure ◽  
Real World ◽  
Ground Truth ◽  
Structural Similarity ◽  
Global Network ◽  
Overlapping Communities ◽  
Detection Algorithms ◽  
First Case ◽  
New Perspective ◽  
The Individual

Abstract The existence of groups of nodes with common characteristics and the relationships between these groups are important factors influencing the structures of social, technological, biological, and other networks. Uncovering such groups and the relationships between them is, therefore, necessary for understanding these structures. Groups can either be found by detection algorithms based solely on structural analysis or identified on the basis of more in-depth knowledge of the processes taking place in networks. In the first case, these are mainly algorithms detecting non-overlapping communities or communities with small overlaps. The latter case is about identifying ground-truth communities, also on the basis of characteristics other than only network structure. Recent research into ground-truth communities shows that in real-world networks, there are nested communities or communities with large and dense overlaps which we are not yet able to detect satisfactorily only on the basis of structural network properties.In our approach, we present a new perspective on the problem of group detection using only the structural properties of networks. Its main contribution is pointing out the existence of large and dense overlaps of detected groups. We use the non-symmetric structural similarity between pairs of nodes, which we refer to as dependency, to detect groups that we call zones. Unlike other approaches, we are able, thanks to non-symmetry, accurately to describe the prominent nodes in the zones which are responsible for large zone overlaps and the reasons why overlaps occur. The individual zones that are detected provide new information associated in particular with the non-symmetric relationships within the group and the roles that individual nodes play in the zone. From the perspective of global network structure, because of the non-symmetric node-to-node relationships, we explore new properties of real-world networks that describe the differences between various types of networks.

A CONNECTIONIST ABM OF SOCIAL CATEGORIZATION PROCESSES

2012 ◽  
Vol 15 (06) ◽  
pp. 1250077 ◽  
Author(s):  
DIRK VAN ROOY
Keyword(s):  
Social Influence ◽  
Network Structure ◽  
Social Adaptation ◽  
Multiple Sources ◽  
Agent Based ◽  
Individual Level ◽  
Extensive Research Program ◽  
Micro Level ◽  
The Individual ◽  
Over Time

This paper introduces a connectionist Agent-Based Model (cABM) that incorporates detailed, micro-level understanding of social influence processes derived from laboratory studies and that aims to contextualize these processes in such a way that it becomes possible to model multidirectional, dynamic influences in extended social networks. At the micro-level, agent processes are simulated by recurrent auto-associative networks, an architecture that has a proven ability to simulate a variety of individual psychological and memory processes [D. Van Rooy, F. Van Overwalle, T. Vanhoomissen, C. Labiouse and R. French, Psychol. Rev. 110, 536 (2003)]. At the macro-level, these individual networks are combined into a "community of networks" so that they can exchange their individual information with each other by transmitting information on the same concepts from one net to another. This essentially creates a network structure that reflects a social system in which (a collection of) nodes represent individual agents and the links between agents the mutual social influences that connect them [B. Hazlehurst, and E. Hutchins, Lang. Cogn. Process. 13, 373 (1998)]. The network structure itself is dynamic and shaped by the interactions between the individual agents through simple processes of social adaptation. Through simulations, the cABM generates a number of novel predictions that broadly address three main issues: (1) the consequences of the interaction between multiple sources and targets of social influence (2) the dynamic development of social influence over time and (3) collective and individual opinion trajectories over time. Some of the predictions regarding individual level processes have been tested and confirmed in laboratory experiments. In a extensive research program, data is currently being collected from real groups that will allow validating the predictions of cABM regarding aggregate outcomes.

scholarly journals Offspring social network structure predicts fitness in families

2012 ◽  
Vol 279 (1749) ◽  
pp. 4914-4922 ◽  
Author(s):  
Nick J. Royle ◽  
Thomas W. Pike ◽  
Philipp Heeb ◽  
Heinz Richner ◽  
Mathias Kölliker
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Conflicts Of Interest ◽  
Parus Major ◽  
Social Structures ◽  
Emergent Properties ◽  
Social Network Structure ◽  
The Social ◽  
The Individual

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

scholarly journals Development of an individual-based model for polioviruses: implications of the selection of network type and outcome metrics

2010 ◽  
Vol 139 (6) ◽  
pp. 836-848 ◽  
Author(s):  
H. RAHMANDAD ◽  
K. HU ◽  
R. J. DUINTJER TEBBENS ◽  
K. M. THOMPSON
Keyword(s):  
Network Structure ◽  
Critical Role ◽  
State Transitions ◽  
Different Types ◽  
Support Policy ◽  
The Individual ◽  
The Impact ◽  
Potential Use ◽  
Selection Of ◽  
Outcome Metrics

SUMMARYWe developed an individual-based (IB) model to explore the stochastic attributes of state transitions, the heterogeneity of the individual interactions, and the impact of different network structure choices on the poliovirus transmission process in the context of understanding the dynamics of outbreaks. We used a previously published differential equation-based model to develop the IB model and inputs. To explore the impact of different types of networks, we implemented a total of 26 variations of six different network structures in the IB model. We found that the choice of network structure plays a critical role in the model estimates of cases and the dynamics of outbreaks. This study provides insights about the potential use of an IB model to support policy analyses related to managing the risks of polioviruses and shows the importance of assumptions about network structure.

scholarly journals A Network Model of Credit Risk Contagion

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Ting-Qiang Chen ◽  
Jian-Min He
Keyword(s):  
Credit Risk ◽  
Numerical Simulations ◽  
Network Model ◽  
Financial Market ◽  
Network Structure ◽  
Stochastic Dominance ◽  
Individual Attitude ◽  
Individual Ability ◽  
The Individual ◽  
Credit Risk Contagion

A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

scholarly journals Recurrence in the evolution of air transport networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kashin Sugishita ◽  
Naoki Masuda
Keyword(s):  
Network Structure ◽  
Airline Industry ◽  
Air Transport ◽  
Transport Networks ◽  
Corporate Strategies ◽  
Airline Alliances ◽  
Network Change ◽  
Air Transport Networks ◽  
The Individual ◽  
Over Time

AbstractChanges in air transport networks over time may be induced by competition among carriers, changes in regulations on airline industry, and socioeconomic events such as terrorist attacks and epidemic outbreaks. Such network changes may reflect corporate strategies of each carrier. In the present study, we propose a framework for analyzing evolution patterns in temporal networks in discrete time from the viewpoint of recurrence. Recurrence implies that the network structure returns to one relatively close to that in the past. We applied the proposed methods to four major carriers in the US from 1987 to 2019. We found that the carriers were different in terms of the autocorrelation, strength of periodicity, and changes in these quantities across decades. We also found that the network structure of the individual carriers abruptly changes from time to time. Such a network change reflects changes in their operation at their hub airports rather than famous socioeconomic events that look closely related to airline industry. The proposed methods are expected to be useful for revealing, for example, evolution of airline alliances and responses to natural disasters or infectious diseases, as well as characterizing evolution of social, biological, and other networks over time.

scholarly journals Constructing Local Cell Specific Networks from Single Cell Data

2021 ◽  
Author(s):  
Xuran Wang ◽  
David Choi ◽  
Kathryn Roeder
Keyword(s):  
Single Cell ◽  
Network Structure ◽  
Gene Networks ◽  
Fetal Brain ◽  
Autism Spectrum ◽  
Cellular Level ◽  
Gene Block ◽  
Local Cell ◽  
The Individual ◽  
Downstream Analysis

ABSTRACTGene co-expression networks yield critical insights into biological processes, and single-cell RNA sequencing provides an opportunity to target inquiries at the cellular level. However, due to the sparsity and heterogeneity of transcript counts, it is challenging to construct accurate gene networks. We develop an approach that estimates cell-specific networks (CSN) for each cell using a method inspired by Dai et al. (7). Although individual CSNs are estimated with considerable noise, average CSNs provide stable estimates of network structure, which provide better estimates of gene block structures than traditional measures. The method, called locCSN, is based on a non-parametric investigation of the joint distribution of gene expression, hence it can readily detect nonlinear correlations, and it is more robust to distributional challenges. The individual networks preserve information about the heterogeneity of the cells and having repeated estimates of network structure facilitates testing for difference in network structure between groups of cells. The original CSN algorithm showed promise; however, it had shortcomings which locCSN overcomes. Additionally, we propose new downstream analysis methods using CSNs, to utilize more fully the information contained within them. Finally, to further our understanding of autism spectrum disorder we examined the evolution of gene networks in fetal brain cells and compared the CSNs of cells sampled from case and control subjects to reveal intriguing patterns in gene co-expression changes.

Professional Networks and Street-Level Performance

2016 ◽  
Vol 47 (1) ◽  
pp. 79-101 ◽  
Author(s):  
Michael D. Siciliano
Keyword(s):  
Public Schools ◽  
Network Structure ◽  
Value Added ◽  
Professional Networks ◽  
Data Set ◽  
Street Level ◽  
Student Test ◽  
The Individual ◽  
Implementation Resources ◽  
Level Performance

Given the complexity of their work, street-level bureaucrats rely on their professional networks to access implementation resources and information. Despite the acknowledged importance of these networks, little research exists on how network structure and composition influence frontline performance. This study analyzes a unique data set that includes the professional networks of more than 420 teachers in 21 public schools along with 3 years of administrative data on student test scores and student demographics. Using value-added models derived from the student test data, objective measures of teacher performance were calculated. The results suggest that street-level performance is influenced by both network structure and composition. Thus, the actions of street-level workers are not independent responses to individual dilemmas, but rather are developed and shaped by specific features of the social structure in which the individual bureaucrat is embedded.

New Technique to Quantitatively Characterize Crosslink Density in IR and Brominated Poly(Isobutylene-CO-Paramethyl Styrene) Blends

1997 ◽  
Vol 70 (4) ◽  
pp. 663-670 ◽  
Author(s):  
Yu F. Wang ◽  
Hsien C. Wang
Keyword(s):  
Molecular Weight ◽  
Network Structure ◽  
Crosslink Density ◽  
Volume Fraction ◽  
Processing Condition ◽  
Product Attributes ◽  
Rubber Blends ◽  
Individual Phase ◽  
Condition Optimization ◽  
The Individual

Abstract The physical properties and application performance of rubber blends are highly dependent on the curing behavior of blend components, morphology, and network structure. Crosslink density or molecular weight between crosslinks characterizes the network structure. It is desirable to develop correlations between product attributes, such as flex, ozone resistance, and permeability with crosslink density of the individual phase in the blend. This will aid developing high performance rubber blends via curative systems, elastomer components and concentration, bromine composition distribution, and processing condition optimization. One major road block is to quantitatively and unambiguously measure the individual phase crosslink density in the blend. A method has been developed and verified with solvent freezing point depression technique. The method can quantitatively determine the individual phase crosslink density in polyisoprene (IR)/Brominated Poly-(isobutylene-co-paramethyl styrene) (BIMS) blends. The method is based on the principle that the molecular weight between crosslinks does not change in different solvents. This is coupled with mass balance equations to determine rubber volume fraction of each phase in the swollen blends. The crosslink density of each phase is then calculated by the Flory-Rehner equation. The method can evaluate the effect of curative distribution, processing conditions, and curative systems on GPR/BIMS blend performance. IR and BIMS blends were cured with zinc oxide and sulfur in this study. It was found that the IR and BIMS phase crosslink density reaches a plateau when the amount of the curing agent is greater or equal to 1.25 phr. The IR phase has a greater crosslinking density than the BIMS phase in the blends. These are valuable information to optimize the curative systems and enhance product attributes.

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