A NEW DYNAMIC COMMUNITY MODEL FOR SOCIAL NETWORKS

2014 ◽  
Vol 25 (02) ◽  
pp. 1350088 ◽  
Author(s):  
ZHE-MING LU ◽  
ZHEN WU ◽  
SHI-ZE GUO ◽  
ZHE CHEN ◽  
GUANG-HUA SONG
Keyword(s):  
Social Networks ◽  
Average Distance ◽  
Small World ◽  
Clustering Coefficient ◽  
Community Model ◽  
Network Diameter ◽  
Proposed Model ◽  
Small World Property ◽  
Two Parameters ◽  
Dynamic Community

In this paper, based on the phenomenon that individuals join into and jump from the organizations in the society, we propose a dynamic community model to construct social networks. Two parameters are adopted in our model, one is the communication rate Pa that denotes the connection strength in the organization and the other is the turnover rate Pb, that stands for the frequency of jumping among the organizations. Based on simulations, we analyze not only the degree distribution, the clustering coefficient, the average distance and the network diameter but also the group distribution which is closely related to their community structure. Moreover, we discover that the networks generated by the proposed model possess the small-world property and can well reproduce the networks of social contacts.

Improved community model for social networks based on social mobility

2015 ◽  
Vol 26 (02) ◽  
pp. 1550012
Author(s):  
Zhe-Ming Lu ◽  
Zhen Wu ◽  
Hao Luo ◽  
Hao-Xian Wang
Keyword(s):  
Social Networks ◽  
Social Mobility ◽  
Turnover Rate ◽  
Small World ◽  
Community Size ◽  
Community Model ◽  
Proposed Model ◽  
Small World Property ◽  
The Relationship ◽  
Group Distribution

This paper proposes an improved community model for social networks based on social mobility. The relationship between the group distribution and the community size is investigated in terms of communication rate and turnover rate. The degree distributions, clustering coefficients, average distances and diameters of networks are analyzed. Experimental results demonstrate that the proposed model possesses the small-world property and can reproduce social networks effectively and efficiently.

THE SMALL-WORLD PROPERTY IN NETWORKS GROWING BY ACTIVE EDGES

2011 ◽  
Vol 14 (06) ◽  
pp. 853-869 ◽  
Author(s):  
PHILIPPE J. GIABBANELLI
Keyword(s):  
Growth Mechanism ◽  
Average Distance ◽  
Network Models ◽  
Small World ◽  
Clustering Coefficient ◽  
Small World Networks ◽  
Fractal Approach ◽  
Small World Property ◽  
Complex Network Models ◽  
Similar Growth

In the last three years, we have witnessed an increasing number of complex network models based on a 'fractal' approach, in which parts of the network are repeatedly replaced by a given pattern. Our focus is on models that can be defined by repeatedly adding a pattern network to selected edges, called active edges. We prove that when a pattern network has at least two active edges, then the resulting network has an average distance at most logarithmic in the number of nodes. This suggests that real-world networks based on a similar growth mechanism are likely to have small average distance. We provide an estimate of the clustering coefficient and verify its accuracy using simulations. Using numerous examples of simple patterns, our simulations show various ways to generate small-world networks. Finally, we discuss extensions to our framework encompassing probabilistic patterns and active subnetworks.

A NETWORK MODEL GENERATED FROM THE RECURSIVE GRAPH BASED ON POLYGON

2013 ◽  
Vol 24 (09) ◽  
pp. 1350062 ◽  
Author(s):  
YUANYUAN SUN ◽  
KAINING HOU ◽  
YUJIE ZHAO
Keyword(s):  
Real Life ◽  
Network Models ◽  
Small World ◽  
Mapping Method ◽  
Clustering Coefficient ◽  
Research Fields ◽  
Network Diameter ◽  
Degree Correlations ◽  
New Perspective ◽  
Small World Property

The study of network models is one of the most challenging research fields among the studies of complex networks, which have been the hot research topics in recent decades. In this paper, we construct a deterministic network by a mapping method based on a recursive graph, and analyze its topological characteristics, including degree distribution, clustering coefficient, network diameter, average path length and degree correlations. We obtain that this network has the small-world property and positive correlation. The network modeling as we present gives a new perspective on networks, and helps to understand better the evolutions of the real-life systems, making it possible to explore the complexity of complex systems.

scholarly journals Models And Mining Of On-Line Social Networks

2021 ◽  
Author(s):  
Yanhua Tian
Keyword(s):  
Social Networks ◽  
Power Law ◽  
Degree Distribution ◽  
Small World ◽  
Spectral Expansion ◽  
On Line ◽  
Simulation Results ◽  
Small World Property ◽  
P Type ◽  
Law Degree

Power law degree distribution, the small world property, and bad spectral expansion are three of the most important properties of On-line Social Networks (OSNs). We sampled YouTube and Wikipedia to investigate OSNs. Our simulation and computational results support the conclusion that OSNs follow a power law degree distribution, have the small world property, and bad spectral expansion. We calculated the diameters and spectral gaps of OSNs samples, and compared these to graphs generated by the GEO-P model. Our simulation results support the Logarithmic Dimension Hypothesis, which conjectures that the dimension of OSNs is m = [log N]. We introduced six GEO-P type models. We ran simulations of these GEO-P-type models, and compared the simulated graphs with real OSN data. Our simulation results suggest that, except for the GEO-P (GnpDeg) model, all our models generate graphs with power law degree distributions, the small world property, and bad spectral expansion.

scholarly journals Directed random geometric graphs

2019 ◽  
Vol 7 (5) ◽  
pp. 792-816
Author(s):  
Jesse Michel ◽  
Sushruth Reddy ◽  
Rikhav Shah ◽  
Sandeep Silwal ◽  
Ramis Movassagh
Keyword(s):  
Real World ◽  
Word Association ◽  
Graph Model ◽  
Small World ◽  
Geometric Graph ◽  
Clustering Coefficient ◽  
Random Geometric Graph ◽  
Random Geometric Graphs ◽  
Scale Free ◽  
Small World Property

Abstract Many real-world networks are intrinsically directed. Such networks include activation of genes, hyperlinks on the internet and the network of followers on Twitter among many others. The challenge, however, is to create a network model that has many of the properties of real-world networks such as power-law degree distributions and the small-world property. To meet these challenges, we introduce the Directed Random Geometric Graph (DRGG) model, which is an extension of the random geometric graph model. We prove that it is scale-free with respect to the indegree distribution, has binomial outdegree distribution, has a high clustering coefficient, has few edges and is likely small-world. These are some of the main features of aforementioned real-world networks. We also empirically observed that word association networks have many of the theoretical properties of the DRGG model.

SYNCHRONIZATION IN THE FAMILY OF CHAOTIC SMALL-WORLD NETWORKS

2008 ◽  
Vol 19 (01) ◽  
pp. 111-123 ◽  
Author(s):  
LIANGMING HE ◽  
DUANWEN SHI
Keyword(s):  
Chaotic System ◽  
Average Distance ◽  
Small World ◽  
Clustering Coefficient ◽  
Small World Networks ◽  
Characteristic Path Length ◽  
Unified Chaotic System ◽  
The Family ◽  
Regular Networks ◽  
High Degree

In this paper we investigate by computer simulation the synchronizability of the family of small-world networks, which consists of identical chaotic units, such as the Lorenz chaotic system, the Chen chaotic system, Lü chaotic system, and the unified chaotic system (unit). It is shown that for weak coupling, synchronization clusters emerge in the networks whose disorder probabilities p are large but do not emerge in the networks whose disorder probabilities p are small; while for strong coupling under which the regular networks do not exhibit synchronization, all dynamical nodes, behaving as in the random networks, mutually synchronize in the networks which own very small disorder probability p and have both high degree of clustering and small average distance. Based on the concepts of clustering coefficient C(p), characteristic path length L(p) and global efficiency E(G), these phenomena are discussed briefly.

scholarly journals Study on Incompatibility of Traditional Chinese Medicine: Evidence from Formula Network, Chemical Space, and Metabolism Room

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Long ◽  
Xiao-Dong Zhang ◽  
Hong-Ying Wu ◽  
Jin Jin ◽  
Guang-Yun Yu ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Complex Network ◽  
Chemical Space ◽  
Average Distance ◽  
Average Degree ◽  
Clustering Coefficient ◽  
The Other ◽  
Network Diameter ◽  
Lines Of Evidence

A traditional Chinese medicine (TCM) formula network including 362 TCM formulas was built by using complex network methodologies. The properties of this network were analyzed including network diameter, average distance, clustering coefficient, and average degree. Meanwhile, we built a TCM chemical space and a TCM metabolism room under the theory of chemical space. The properties of chemical space and metabolism room were calculated and analyzed. The properties of the medicine pairs in “eighteen antagonisms and nineteen mutual inhibitors,” an ancient rule for TCM incompatibility, were studied based on the TCM formula network, chemical space, and metabolism room. The results showed that the properties of these incompatible medicine pairs are different from those of the other TCM based on the analysis of the TCM formula network, chemical space, and metabolism room. The lines of evidence derived from our work demonstrated that the ancient rule of TCM incompatibility, “eighteen antagonisms and nineteen mutual inhibitors,” is probably scientifically based.

Abstract 663: Metabolomics And Correlation Network Analysis Of Hypertension

Hypertension ◽  
2014 ◽  
Vol 64 (suppl_1) ◽  
Author(s):  
zhongmin tian ◽  
le wang ◽  
entai hou ◽  
qiong sun
Keyword(s):  
Amino Acids ◽  
Comprehensive Evaluation ◽  
Small World ◽  
Clustering Coefficient ◽  
Correlation Network ◽  
Beta Alanine ◽  
Topological Parameters ◽  
Correlation Networks ◽  
Metabolomics Study ◽  
Small World Property

The awareness, treatment and controls rates of hypertension for people in their 20s and 30s age are much lower than average. In this paper, a GC/MS based metabolomics study was performed in plasma of young hypertensive men and age-matched normal ones. Correlations of the identified metabolites were analyzed and visualized. A systematic correlation network was constructed with the significance of correlation coefficient setting at threshold of 0.6. Glycine, lysine, cystine and beta-alanine were selected as the most important nodes of the network, with high values of degree. A relatively short average path length and high clustering coefficient suggested a small-world property of the network. Moreover, differential metabolites in young hypertensive men were used to construct a core correlation network for further understanding. Four hubs (lysine, glycine, cystine and tryptophan) were confirmed by a comprehensive evaluation of three centrality indices. The statistical and topological parameters of the network indicated that local disturbance to hubs would rapidly transfer to the whole network. These results demonstrated that the distinct metabolic profiles of young hypertensive men might be due to perturbation of the biosynthesis pathway of amino acids. Integrated analyses of metabolomics and correlation networks would provide a broadened window for further understanding of hypertension. Key Words: metabolomics; hypertension; correlation network; amino acids; statistical and topological characteristics; centrality indices; hubs

TRAPPING ON WEIGHTED TETRAHEDRON KOCH NETWORKS WITH SMALL-WORLD PROPERTY

Fractals ◽  
2014 ◽  
Vol 22 (01n02) ◽  
pp. 1450006 ◽  
Author(s):  
MEIFENG DAI ◽  
QI XIE ◽  
LIFENG XI
Keyword(s):  
Small World ◽  
Clustering Coefficient ◽  
Weight Factor ◽  
First Passage ◽  
Mean First Passage Times ◽  
Weighted Clustering ◽  
Self Similar ◽  
Small World Property ◽  
Analytical Expressions ◽  
Passage Times

In this paper, we present weighted tetrahedron Koch networks depending on a weight factor. According to their self-similar construction, we obtain the analytical expressions of the weighted clustering coefficient and average weighted shortest path (AWSP). The obtained solutions show that the weighted tetrahedron Koch networks exhibits small-world property. Then, we calculate the average receiving time (ART) on weighted-dependent walks, which is the sum of mean first-passage times (MFPTs) for all nodes absorpt at the trap located at a hub node. We find that the ART exhibits a sublinear or linear dependence on network order.

A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

2018 ◽  
Vol 32 (04) ◽  
pp. 1850029 ◽  
Author(s):  
İlker Türker ◽  
Eyüb Ekmel Sulak
Keyword(s):  
Power Law ◽  
Small World ◽  
Semantic Relations ◽  
Edge Weight ◽  
Friendship Networks ◽  
Multilayer Network ◽  
Network Diameter ◽  
Single Entry ◽  
Interdisciplinary Framework ◽  
Small World Property

Complex network studies, as an interdisciplinary framework, span a large variety of subjects including social media. In social networks, several mechanisms generate miscellaneous structures like friendship networks, mention networks, tag networks, etc. Focusing on tag networks (namely, hashtags in twitter), we made a two-layer analysis of tag networks from a massive dataset of Twitter entries. The first layer is constructed by converting the co-occurrences of these tags in a single entry (tweet) into links, while the second layer is constructed converting the semantic relations of the tags into links. We observed that the universal properties of the real networks like small-world property, clustering and power-law distributions in various network parameters are also evident in the multilayer network of hashtags. Moreover, we outlined that co-occurrences of hashtags in tweets are mostly coupled with semantic relations, whereas a small number of semantically unrelated, therefore random links reduce node separation and network diameter in the co-occurrence network layer. Together with the degree distributions, the power-law consistencies of degree difference, edge weight and cosine similarity distributions in both layers are also appealing forms of Zipf’s law evident in nature.

Sign in / Sign up

Export Citation Format

Share Document