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Ying Fan

Publications and source records attributed to Ying Fan.

80 records · Page 5Linked to original sources

The Role of Weight on Community Structure of Networks

The role of weight on the weighted networks is investigated by studying the effect of weight on community structures. We use weighted modularity $Q^w$ to evaluate the partitions and Weighted Extremal Optimization algorithm to detect communities. Starting from idealized and empirical weighted networks, the distribution or matching between weights and edges are disturbed. Using dissimilarity function $D$ to distinguish the difference between community structures, it is found that the redistribution of weights does strongly affect the community structure especially in dense networks. This indicates that the community structure in networks is a suitable property to reflect the role of weight.

physics.soc-ph↗

Accuracy and Precision of Methods for Community Identification in Weighted Networks

Based on brief review of approaches for community identification and measurement for sensitivity characterization, the accuracy and precision of several approaches for detecting communities in weighted networks are investigated. In weighted networks, the community structure should take both links and link weights into account and the partition of networks should be evaluated by weighted modularity $Q^w$. The results reveal that link weight has important effects on communities especially in dense networks. Potts model and Weighted Extremal Optimization (WEO) algorithm work well on weighted networks. Then Potts model and WEO algorithms are used to detect communities in Rhesus monkey network. The results gives nice understanding for real community structure.

physics.soc-ph↗

Effects of Weight on Structure and Dynamics in Complex Networks

Link weight is crucial in weighted complex networks. It provides additional dimension for describing and adjusting the properties of networks. The topological role of weight is studied by the effects of random redistribution of link weights based on regular network with initial homogeneous weight. The small world effect emerges due to the weight randomization. Its effects on the dynamical systems coupled by weighted networks are also investigated. Randomization of weight can increase the transition temperature in Ising model and enhance the ability of synchronization of chaotic systems dramatically.

cond-mat.stat-mech↗

The Community Structure of Econophysicist Collaboration Networks

This paper uses a database of collaboration recording between Econophysics Scientists to study the community structure of this collaboration network, which with a single type of vertex and a type of undirected, weighted edge. Hierarchical clustering and the algorithm of Girvan and Newman are presented to analyze the data. And it emphasizes the influence of the weight to results of communities by comparing the different results obtained in different weights. A function D is proposed to distinguish the difference between above results. At last the paper also gives explanation to the results and discussion about community structure.

physics.soc-ph↗

Evolving Model of Weighted Networks Inspired by Scientific Collaboration Networks

Inspired by scientific collaboration networks, especially our empirical analysis of the network of econophysicists, an evolutionary model for weighted networks is proposed. Both degree-driven and weight-driven models are considered. Compared with the BA model and other evolving models with preferential attachment, there are two significant generalizations. First, besides the new vertex added in at every time step, old vertices can also attempt to build up new links, or to reconnect the existing links. The reconnection between both new-old and old-old nodes are recorded and the connecting times on every link is converted into the weight of the link. This provides a natural way for the evolution of edge weight. Second, besides degree and the weight of vertices, a path-related local information is also used as a reference in the preferential attachment. The path-related preferential attachment mechanism significantly increases the clustering coefficient of the network. The model shows the scale-free phenomena in degree and weight distribution. It also gives well qualitatively consistent behavior with the empirical results.

cond-mat.dis-nn↗

Weighted networks of scientific communication: the measurement and geometrical role of weight

In order to take the weight of connection into consideration and to find a natural measurement of weight, we have collected papers in Econophysics and constructed a network of scientific communication to integrate idea transportation among econophysicists by collaboration, citation and personal discussion. Some basic statistics such as weight per degree are discussed in \cite{fan}. In this paper, by including the papers published recently, further statistical results for the network are reported. Clustering coefficient of weighted network is introduced and empirically studied in this network. We also compare the typical statistics on this network under different weight measurements, including random and inverse weight. The conclusion from weight-randomized network is helpful to the investigation of the geometrical role of weight.

cond-mat.other↗

Increasing Returns to Scale, Dynamics of Industrial Structure and Size Distribution of Firms

A model is presented of the market dynamics to emphasis the effects of increasing returns to scale, including the description of the born and death of the adaptive producers. The evolution of market structure and its behavior with the technological shocks are discussed. Its dynamics is in good agreement with some empirical stylized facts of industrial evolution. Together with the diversities of demand and adaptive growth strategies of firms, the generalized model has reproduced the power-law distribution of firm size. Three factors mainly determine the competitive dynamics and the skewed size distributions of firms: 1. Self-reinforcing mechanism; 2. Adaptive firm grows strategies; 3. Demand diversities or widespread heterogeneity in the technological capabilities of different firms. Key words: Econophysics, Increasing returns, Industry dynamics, Size distribution of firms

cond-mat.stat-mech↗

Network of Econophysicists: a weighted network to investigate the development of Econophysics

The development of Econophysics is studied from the perspective of scientific communication networks. Papers in Econophysics published from 1992 to 2003 are collected. Then a weighted and directed network of scientific communication, including collaboration, citation and personal discussion, is constructed. Its static geometrical properties, including degree distribution, weight distribution, weight per degree, and betweenness centrality, give a nice overall description of the research works. The way we introduced here to measure the weight of connections can be used as a general one to construct weighted network.

cond-mat.soft↗