Networks: An Introduction

By Mark Newman. 2010

11,668 citations recorded by the source corpus.

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models (2018, methodology): “graphs based on a priori structural assumptions (Newman, 2010).”
Human mobility: Models and applications (2017, background): “Compared to CDR’s, data collected from OSN’s and LBSN’s, have the advantage of having more contextual information associated with the geographical positions and the users, enabling the study of mobility in a broader context.”
How well do network models predict observations? On the importance of predictability in network models (2016, unknown): “In addition, network models open up the possibility to study the network structure: for instance, one can use network summary measures like density or centrality to describe the global structure of the network (Newman, 2010).”
A Time-dependent SIR model for COVID-19 (2020, unknown): “在流行病的典型數學表示中,我們會將疾病的動態改變簡化為幾種基本的疾病狀態。其中一個簡單的版本便是將疾病的狀態分成三個狀態的 Susceptible-infectedrecovered (SIR) model [11],三個狀態分別是 susceptible、 infected 和 recovered。我們將一個在 t 時間尚未得病, 但若接觸感染者便有可能得病的狀態稱作 susceptible; infected 態是指在 t 時間一個患有疾病,且具傳染能力的個體,若與 susceptible態的個體接觸,有一定的可能將其傳染的狀態;recovered態則是在 t時間從 infecte”
Spatial Science and Network Science: Review and Outcomes of a Complex Relationship (2014, background): “SWNs and SFNs have in common several features (see Newman, 2010 for a useful synthesis).”
Regularized Gaussian Psychological Networks: Brief Report on the Performance of Extended BIC Model Selection (2016, methodology): “These models strikingly differ from typically used network models such as social networks (Wasserman and Faust, 1994) or transportation networks (Newman, 2010), in that variables are not static entities (e.”
R&D Networks: Theory, Empirics, and Policy Implications (2019, unknown): “See Newman [2002] and Pastor-Satorras et al.”
Iterative ranking from pair-wise comparisons (2012, background): “Such an interpretation of the stationary distribution of a Markov chain or a random walk has been an effective measure of relative importance of a node in wide class of graph problems, popularly known as the network centrality [13].”
A simple, distance-dependent formulation of the Watts-Strogatz model for directed and undirected small-world networks (2014, background): “In the directed case where In the undirected case we have the simpler expression which corresponds to the classical deﬁnition of transitivity for undirected networks [1, 6].”
Hive plots - rational approach to visualizing networks (2012, unknown): “tissue [1–3].”
Universality in network dynamics (2013, background): “In such networks the number of nodes at distance l from a node follows [5] Barzel and Barabási Page 5”
Dynamic scheduling of network updates (2014, methodology): “We use centrality [22] to decide the order of the iteration; the intuition is that a central node of an SCC is on many cycles, and if we can schedule this node early, many cycles will disappear and we can finish the SCC quickly.”
What do centrality measures measure in psychological networks? (2019, methodology): “One could study, for example, if schoolchildren are more likely to be friends with schoolmates of the same gender (Moreno, 1934; Newman, 2010).”
OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks (2016, unknown): “Most large real-world networks are complex (Newman, 2010).”