Complex Networks: Structure and Dynamics

By Shilpa Chakravartula. 2014

3,370 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4aa76afb4df52271947b17f88dbd6afca43ddb9b

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Citations in the corpus

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks (2014, methodology): “As the intensity is increased, there is a qualitative change in the system dynamics, characterized by a monotonic increase in the number of signal units in the network until all buffers are filled, leading to ‘‘jamming’’ [2,20].”
Activity driven modeling of time varying networks (2012, background): “(4) by considering b 5 lÆkæ, ai 5 gxi and Ækæ 5 2mgÆxæ.”
Core-Periphery Structure in Networks (2012, background): “When representing a network as a graph, all of the connections are pairwise and hence represented by ties known as edges [5, 43].”
The science of science: from the perspective of complex systems (2017, background): “Similar to other real systems such as power grids, airlines, and the Internet, the science system is also an ideal system that should bemodeled by complex networks [10].”
Dynamics on higher-order networks: a review (2022, background): “Indeed, network science has proven highly efficient in elucidating the dynamics of complex systems arising from many different contexts in the physical, biological as well as technological and social sciences [3,4].”
Defining and identifying Sleeping Beauties in science (2015, background): “The criterion, now widely referred to as preferential attachment, was recently popularized by Barabási and Albert (19), who proposed it as a general mechanism that yields heterogeneous connectivity patterns in networks describing systems in various domains (20, 21).”
Deconstructing the construct: A network perspective on psychological phenomena (2013, unknown): “variance. Reflective models are commonly presented as ‘measurementmodels’ inmodern test theory (Mellenbergh, 1994). Examples are the IRT models of Rasch (1960), Birnbaum (1968) and Samejima (1969), common factor models (Jöreskog, 1971; Lawley & Maxwell, 1963), latent class models (Lazarsfeld, 1959),”
Recommender Systems (2012, background): “Physicists, with their long experience with data-driven research, have joined this trend and contributed to many fields such as finance [3, 4], network theory [5, 6, 7, 8, 9] and social dynamics [10] which are outside their traditional realm.”
Investigating the structure of semantic networks in low and high creative persons (2014, methodology): “This model has successfully described a wide range of sociological, technological, biological and economical networks (Boccaletti et al., 2006; Cohen and Havlin, 2010; Kenett et al., 2010; Newman, 2010) and is also widely used in studying structural and functional brain networks (Sporns, 2011;…”
The structure and dynamics of multilayer networks (2014, methodology): “[396] the reader can find an interesting study on the Master Stability Function for class III systems [9].”
Analysis and Control of Epidemics: A Survey of Spreading Processes on Complex Networks (2015, background): “The main focus of this article is on agent-based models, where individuals can randomly move from one compartment to another with some defined rates rather than deterministically, since stochastic models can better capture the dynamics of a spreading disease, such as influenza.”
Clustering and Community Detection in Directed Networks: A Survey (2013, background): “ of a community/cluster in undirected networks. Table1gives a list of used symbols along with their denition. For a general introduction to the eld of complex networks, the reader may refer to Refs. [26,1,27]. 2.1. Graph Theory A network is usually represented by a graph (throughout the paper we use”
Controlling edge dynamics in complex networks (2011, background): “The last decade has witnessed an explosive growth of interest in the descriptive analysis of complex natural and technological systems that permeate many aspects of everyday life [3, 11, 42].”