Identifying high betweenness centrality nodes in large social networks
نویسندگان
چکیده
منابع مشابه
Approximating Betweenness Centrality in Large Evolving Networks
Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in large networks. For static networks, approximation based on randomly sampled paths has been shown to be significantly faster in practice. However, for dynamic networks, no approximation algorithm for betweenness centrali...
متن کاملBetweenness centrality in large complex networks
We analyze the betweenness centrality (BC) of nodes in large complex networks. In general, the BC is increasing with connectivity as a power law with an exponent η. We find that for trees or networks with a small loop density η = 2 while a larger density of loops leads to η < 2. For scale-free networks characterized by an exponent γ which describes the connectivity distribution decay, the BC is...
متن کاملBetweenness centrality correlation in social networks.
Scale-free (SF) networks exhibiting a power-law degree distribution can be grouped into the assortative, dissortative, and neutral networks according to the behavior of the degree-degree correlation coefficient. Here we investigate the betweenness centrality (BC) correlation for each type of SF networks. While the BC-BC correlation coefficients behave similarly to the degree-degree correlation ...
متن کاملFast Computing Betweenness Centrality with Virtual Nodes on Large Sparse Networks
Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses O(N(M + N log N)) time and O(N + M) space for weighted networks, where N and M are the number of nodes and edges in the network, respectively. By inserting virtual nodes into the weighted edges and transfor...
متن کاملMetropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks
Betweenness centrality is an important index widely used in different domains such as social networks, traffic networks and the world wide web. However, even for mid-size networks that have only a few hundreds thousands vertices, it is computationally expensive to compute exact betweenness scores. Therefore in recent years, several approximate algorithms have been developed. In this paper, firs...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Social Network Analysis and Mining
سال: 2012
ISSN: 1869-5450,1869-5469
DOI: 10.1007/s13278-012-0076-6