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Open AccessJournal ArticleDOI

Fast algorithm for detecting community structure in networks.

Mark Newman
- 18 Jun 2004 - 
- Vol. 69, Iss: 6, pp 066133-066133
TLDR
An algorithm is described which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster, than previous algorithms.
Abstract
Many networks display community structure--groups of vertices within which connections are dense but between which they are sparser--and sensitive computer algorithms have in recent years been developed for detecting this structure. These algorithms, however, are computationally demanding, which limits their application to small networks. Here we describe an algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster, than previous algorithms. We give several example applications, including one to a collaboration network of more than 50,000 physicists.

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Citations
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Journal ArticleDOI

Visual Exploration of Complex Time-Varying Graphs

TL;DR: This work exploits the structure of these graphs with a two-level approach to drawing, where the graph is decomposed into a tree of biconnected components, and performs an order of magnitude faster than the best previous approaches.
Journal ArticleDOI

Dynamic Social Community Detection and Its Applications

TL;DR: Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs, is presented.
Journal ArticleDOI

“Technology enabled Health” – Insights from twitter analytics with a socio-technical perspective

TL;DR: This study focuses on exploring the health technology related discussions in Twitter by mining tweets and presents the top technologies in health domain through hashtag analysis and top diseases through word analysis and their association through co-occurrence of words within the tweets.
Journal ArticleDOI

Precedent in International Courts: A Network Analysis of Case Citations by the European Court of Human Rights

TL;DR: In this paper, a network analysis of European Court of Human Rights (ECtHR) citations was conducted to investigate the role of case citations in the legitimacy of international judgments. But the authors were unable to identify the most prolific international court in the human rights domain.
References
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疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

宁北芳, +1 more
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Journal ArticleDOI

Statistical mechanics of complex networks

TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Journal ArticleDOI

The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

Community structure in social and biological networks

TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
Journal ArticleDOI

Finding and evaluating community structure in networks.

TL;DR: It is demonstrated that the algorithms proposed are highly effective at discovering community structure in both computer-generated and real-world network data, and can be used to shed light on the sometimes dauntingly complex structure of networked systems.
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