SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

2009 ◽  
Vol 20 (06) ◽  
pp. 979-990 ◽  
Author(s):  
FABIO STUCCHI VANNUCCHI ◽  
CARMEN P. C. PRADO
Keyword(s):  
Community Structure ◽  
Order Parameter ◽  
High Dimensionality ◽  
Power Law Distribution ◽  
Scale Free ◽  
Absorbing State ◽  
Regular Lattices ◽  
Scale Properties ◽  
Proportional Elections

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.

Cascading failures in complex networks with community structure

2014 ◽  
Vol 25 (05) ◽  
pp. 1440005 ◽  
Author(s):  
Guoqiang Lin ◽  
Zengru Di ◽  
Ying Fan
Keyword(s):  
Community Structure ◽  
Community Networks ◽  
Random Networks ◽  
Cascading Failures ◽  
Power Law Distribution ◽  
Avalanche Size ◽  
Scale Free ◽  
High Betweenness ◽  
Failure Scenario ◽  
The Relationship

Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable. Understanding what will affect cascading failures and how to protect or attack networks with strong community structure is therefore of interest. In this paper, we have constructed scale-free Community Networks (SFCN) and Random Community Networks (RCN). We applied these networks, along with the Lancichinett–Fortunato–Radicchi (LFR) benchmark, to the cascading-failure scenario to explore their vulnerability to attack and the relationship between cascading failures and the degree distribution and community structure of a network. The numerical results show that when the networks are of a power-law distribution, a stronger community structure will result in the failure of fewer nodes. In addition, the initial removal of the node with the highest betweenness will not lead to the worst cascading, i.e. the largest avalanche size. The Betweenness Overflow (BOF), an index that we developed, is an effective indicator of this tendency. The RCN, however, display a different result. In addition, the avalanche size of each node can be adopted as an index to evaluate the importance of the node.

SYNCHRONIZABILITY OF COMPLEX NETWORKS WITH COMMUNITY STRUCTURE

2012 ◽  
Vol 23 (04) ◽  
pp. 1250029 ◽  
Author(s):  
MAHDI JALILI
Keyword(s):  
Community Structure ◽  
Real World ◽  
Order Parameter ◽  
Small World ◽  
Laplacian Matrix ◽  
Small World Networks ◽  
Scale Free ◽  
Community Connections ◽  
Scale Free Networks ◽  
Kuramoto Oscillators

Many real-world networks show community structure characterized by dense intra-community connections and sparse inter-community links. In this paper we investigated the synchronization properties of such networks. In this work we constructed such networks in a way that they consist of a number of communities with scale-free or small-world structure. Furthermore, with a probability, the intra-community connections are rewired to inter-community links. Two synchronizability measures were considered as the eigenratio of the Laplacian matrix and the phase order parameter obtained for coupled nonidentical Kuramoto oscillators. We found a power-law relation between the eigenratio and the inter-community rewiring probability in which as the rewiring probability increased, the eigenratio decreased, and hence, the synchronizability enhanced. The phase order parameter also increased by increasing the rewiring probability. Also, small-world networks with community structure showed better synchronization properties as compared to scale-free networks with community structure.

scholarly journals SPECTRAL METHODS CLUSTER WORDS OF THE SAME CLASS IN A SYNTACTIC DEPENDENCY NETWORK

2007 ◽  
Vol 17 (07) ◽  
pp. 2453-2463 ◽  
Author(s):  
RAMON FERRER I CANCHO ◽  
ANDREA CAPOCCI ◽  
GUIDO CALDARELLI
Keyword(s):  
Community Structure ◽  
Spectral Methods ◽  
Null Hypothesis ◽  
Cluster Size ◽  
Small World ◽  
Power Law Distribution ◽  
Long Range Correlations ◽  
Scale Free ◽  
Dependency Network ◽  
Syntactic Dependency

We analyze here a particular kind of linguistic network where vertices represent words and edges stand for syntactic relationships between words. The statistical properties of these networks have been recently studied and various features such as the small-world phenomenon and a scale-free distribution of degrees have been found. Our work focuses on four classes of words: verbs, nouns, adverbs and adjectives. Here, we use spectral methods sorting vertices. We show that the ordering clusters words of the same class. For nouns and verbs, the cluster size distribution clearly follows a power-law distribution that cannot be explained by a null hypothesis. Long-range correlations are found between vertices in the ordering provided by the spectral method. The findings support the use of spectral methods for detecting community structure.

An inter-dependence of flood and drought: disentangling amphibian beta diversity in seasonal floodplains

2017 ◽  
Vol 68 (11) ◽  
pp. 2115 ◽  
Author(s):  
Leonardo F. B. Moreira ◽  
Tainá F. Dorado-Rodrigues ◽  
Vanda L. Ferreira ◽  
Christine Strüssmann
Keyword(s):  
Community Structure ◽  
Environmental Factors ◽  
Quantitative Data ◽  
Explanatory Variable ◽  
Biotic Interactions ◽  
Ecological Role ◽  
Β Diversity ◽  
Amphibian Community ◽  
Dry Seasons

Species composition in floodplains is often affected by different structuring factors. Although floods play a key ecological role, habitat selection in the dry periods may blur patterns of biodiversity distribution. Here, we employed a partitioning framework to investigate the contribution of turnover and nestedness to β-diversity patterns in non-arboreal amphibians from southern Pantanal ecoregion. We investigated whether components of β-diversity change by spatial and environmental factors. We sampled grasslands and dense arboreal savannas distributed in 12 sampling sites across rainy and dry seasons, and analysed species dissimilarities using quantitative data. In the savannas, both turnover and nestedness contributed similarly to β diversity. However, we found that β diversity is driven essentially by turnover, in the grasslands. In the rainy season, balanced variation in abundance was more related to altitude and factors that induce spatial patterns, whereas dissimilarities were not related to any explanatory variable during dry season. In the Pantanal ecoregion, amphibian assemblages are influenced by a variety of seasonal constraints on terrestrial movements and biotic interactions. Our findings highlighted the role of guild-specific patterns and indicated that mass effects are important mechanisms creating amphibian community structure in the Pantanal.

scholarly journals Triggering avalanches by transverse perturbations in a rotating drum

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vicente Salinas ◽  
Cristóbal Quiñinao ◽  
Sebastián González ◽  
Gustavo Castillo
Keyword(s):  
Hopf Bifurcation ◽  
Theoretical Model ◽  
Order Parameter ◽  
Small Scale ◽  
Rotating Drum ◽  
Governing Parameter ◽  
Stick Slip ◽  
Slip Regime ◽  
Axis Of Rotation

AbstractWe study the role of small-scale perturbations in the onset of avalanches in a rotating drum in the stick-slip regime. By vibrating the system along the axis of rotation with an amplitude orders of magnitude smaller than the particles’ diameter, we found that the order parameter that properly describes the system is the kinetic energy. We also show that, for high enough frequencies, the onset of the avalanche is determined by the amplitude of the oscillation, contrary to previous studies that showed that either acceleration or velocity was the governing parameter. Finally, we present a theoretical model that explains the transition between the continuous and discrete avalanche regimes as a supercritical Hopf bifurcation.

scholarly journals Stochastic Assembly Leads to Alternative Communities with Distinct Functions in a Bioreactor Microbial Community

mBio ◽  
2013 ◽  
Vol 4 (2) ◽  
Author(s):  
Jizhong Zhou ◽  
Wenzong Liu ◽  
Ye Deng ◽  
Yi-Huei Jiang ◽  
Kai Xue ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Microbial Diversity ◽  
Microbial Community Structure ◽  
Community Assembly ◽  
Ecosystem Functioning ◽  
Dominant Role ◽  
Microbial Biodiversity ◽  
Stochastic Assembly

ABSTRACTThe processes and mechanisms of community assembly and its relationships to community functioning are central issues in ecology. Both deterministic and stochastic factors play important roles in shaping community composition and structure, but the connection between community assembly and ecosystem functioning remains elusive, especially in microbial communities. Here, we used microbial electrolysis cell reactors as a model system to examine the roles of stochastic assembly in determining microbial community structure and functions. Under identical environmental conditions with the same source community, ecological drift (i.e., initial stochastic colonization) and subsequent biotic interactions created dramatically different communities with little overlap among 14 identical reactors, indicating that stochastic assembly played dominant roles in determining microbial community structure. Neutral community modeling analysis revealed that deterministic factors also played significant roles in shaping microbial community structure in these reactors. Most importantly, the newly formed communities differed substantially in community functions (e.g., H2production), which showed strong linkages to community structure. This study is the first to demonstrate that stochastic assembly plays a dominant role in determining not only community structure but also ecosystem functions. Elucidating the links among community assembly, biodiversity, and ecosystem functioning is critical to understanding ecosystem functioning, biodiversity preservation, and ecosystem management.IMPORTANCEMicroorganisms are the most diverse group of life known on earth. Although it is well documented that microbial natural biodiversity is extremely high, it is not clear why such high diversity is generated and maintained. Numerous studies have established the roles of niche-based deterministic factors (e.g., pH, temperature, and salt) in shaping microbial biodiversity, the importance of stochastic processes in generating microbial biodiversity is rarely appreciated. Moreover, while microorganisms mediate many ecosystem processes, the relationship between microbial diversity and ecosystem functioning remains largely elusive. Using a well-controlled laboratory system, this study provides empirical support for the dominant role of stochastic assembly in creating variations of microbial diversity and the first explicit evidence for the critical role of community assembly in influencing ecosystem functioning. The results presented in this study represent important contributions to the understanding of the mechanisms, especially stochastic processes, involved in shaping microbial biodiversity.

A Discovery Method of the Dirty Data Transmission Path Based on Complex Network

2014 ◽  
Vol 651-653 ◽  
pp. 1741-1747
Author(s):  
Xiao Lin Zhao ◽  
Gang Hao ◽  
Chang Zhen Hu ◽  
Zhi Qiang Li
Keyword(s):  
Complex Network ◽  
Data Transmission ◽  
Software System ◽  
Power Law Distribution ◽  
Scale Free ◽  
Transmission Path ◽  
Binary File ◽  
Weighted Directed Graph ◽  
Dirty Data ◽  
Discovery Method

With the increasing scale of software system, the interaction between software elements becomes more and more complex, which lead to the increased dirty data in running software system. This may reduce the system performance and cause system collapse. In this paper, we proposed a discovery method of the dirty data transmission path based on complex network. Firstly, the binary file is decompiled and the function call graph is drawn by using the source code. Then the software structure is described as a weighted directed graph based on the knowledge of complex network. In addition, the dirty data node is marked by using the power-law distribution characteristics of the scale-free network construction of complex network chart. Finally, we found the dirty data transmission path during software running process. The experimental results show the transmission path of dirty data is accurate, which confirmed the feasibility of the method.

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