Consensus dynamics
Consensus dynamics or agreement dynamics is an area of research lying at the intersection of systems theory and graph theory. A major topic of investigation is the agreement or consensus problem in mu
Widest path problem
In graph algorithms, the widest path problem is the problem of finding a path between two designated vertices in a weighted graph, maximizing the weight of the minimum-weight edge in the path. The wid
Incomplete information network game
Network games of incomplete information represent strategic network formation when agents do not know in advance their neighbors, i.e. the network structure and the value stemming from forming links w
K shortest path routing
The k shortest path routing problem is a generalization of the shortest path routing problem in a given network. It asks not only about a shortest path but also about next k−1 shortest paths (which ma
Network medicine
Network medicine is the application of network science towards identifying, preventing, and treating diseases. This field focuses on using network topology and network dynamics towards identifying dis
Sparse network
In network science, a sparse network has much fewer links than the possible maximum number of links within that network (the opposite is a dense network). The study of sparse networks is a relatively
Temporal network
A temporal network, also known as a time-varying network, is a network whose links are active only at certain points in time. Each link carries information on when it is active, along with other possi
Multidimensional network
In network theory, multidimensional networks, a special type of multilayer network, are networks with multiple kinds of relations. Increasingly sophisticated attempts to model real-world systems as mu
Network simplex algorithm
In mathematical optimization, the network simplex algorithm is a graph theoretic specialization of the simplex algorithm. The algorithm is usually formulated in terms of a minimum-cost flow problem. T
Mediation-driven attachment model
In the scale-free network theory (mathematical theory of networks or graph theory), a mediation-driven attachment (MDA) model appears to embody a preferential attachment rule tacitly rather than expli
Longest path problem
In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph. A path is called simple if it does not have any r
Game theory in communication networks
Game theory has been used as a tool for modeling and studying interactions between cognitive radios envisioned to operate in future communications systems. Such terminals will have the capability to a
Robustness of complex networks
Robustness, the ability to withstand failures and perturbations, is a critical attribute of many complex systems including complex networks. The study of robustness in complex networks is important fo
Community search
Discovering communities in a network, known as community detection/discovery, is a fundamental problem in network science, which attracted much attention in the past several decades. In recent years,
Biased random walk on a graph
In network science, a biased random walk on a graph is a time path process in which an evolving variable jumps from its current state to one of various potential new states; unlike in a pure random wa
Link prediction
In network theory, link prediction is the problem of predicting the existence of a link between two entities in a network. Examples of link prediction include predicting friendship links among users i
Network Science CTA
The Network Science Collaborative Technology Alliance (NS CTA) is a collaborative research alliance funded by the US Army Research Laboratory (ARL) and focused on fundamental research on the critical
Gephi
Gephi (/ˈɡɛfi/ GE-fee) is an open-source network analysis and visualization software package written in Java on the NetBeans platform.
Xulvi-Brunet–Sokolov algorithm
Xulvi-Brunet and Sokolov's algorithm generates networks with chosen degree correlations. This method is based on link rewiring, in which the desired degree is governed by parameter ρ. By varying this
Strategic network formation
Strategic network formation defines how and why networks take particular forms. In many networks, the relation between nodes is determined by the choice of the participating players involved, not by a
Fitness model (network theory)
In complex network theory, the fitness model is a model of the evolution of a network: how the links between nodes change over time depends on the fitness of nodes. Fitter nodes attract more links at
Low-degree saturation
In a scale-free network the degree distribution follows a power law function. In some empirical examples this power-law fits the degree distribution well only in the high degree region, however for sm
Degree distribution
In the study of graphs and networks, the degree of a node in a network is the number of connections it has to other nodes and the degree distribution is the probability distribution of these degrees o
Maximal entropy random walk
Maximal entropy random walk (MERW) is a popular type of biased random walk on a graph, in which transition probabilities are chosen accordingly to the principle of maximum entropy, which says that the
Network theory in risk assessment
A network is an abstract structure capturing only the basics of connection patterns and little else. Because it is a generalized pattern, tools developed for analyzing, modeling and understanding netw
Assortative mixing
In the study of complex networks, assortative mixing, or assortativity, is a bias in favor of connections between network nodes with similar characteristics. In the specific case of social networks, a
Betweenness centrality
In graph theory, betweenness centrality (or "betweeness centrality") is a measure of centrality in a graph based on shortest paths. For every pair of vertices in a connected graph, there exists at lea
Social network
A social network is a social structure made up of a set of social actors (such as individuals or organizations), sets of dyadic ties, and other social interactions between actors. The social network p
Complex network zeta function
Different definitions have been given for the dimension of a complex network or graph. For example, metric dimension is defined in terms of the resolving set for a graph. Dimension has also been defin
Attack tolerance
In the context of complex networks, attack tolerance is the network's robustness meaning the ability to maintain the overall connectivity and diameter of the network as nodes are removed. Several grap
Sink (computing)
In computing, a sink, or data sink generally refers to the destination of data flow. The word sink has multiple uses in computing. In software engineering, an event sink is a class or function that re
Centrality
In graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most inf
Phenotypic disease network (PDN)
The first phenotypic disease network was constructed by Hidalgo et al. (2009) to help understand the origins of many diseases and the links between them. Hidalgo et al. (2009) defined diseases as spec
Quantum complex network
Quantum complex networks are complex networks whose nodes are quantum computing devices. Quantum mechanics has been used to create secure quantum communications channels that are protected from hackin
Network Description Language
Network Description Language (NDL) is a tool to reduce the complexity as networks evolve into the future. NDL enables both humans and machines to have a better grasp on today’s highly evolved networks
Weighted planar stochastic lattice
Physicists often use various lattices to apply their favorite models in them. For instance, the most favorite lattice is perhaps the square lattice. There are 14 Bravais space lattice where every cell
Climate as complex networks
The field of complex networks has emerged as an important area of science to generate novel insights into nature of complex systems The application of network theory to climate science is a young and
Critical point (network science)
In network science, a critical point is a value of , which separates random networks that have a giant component from those that do not (i.e. it separates a network in a subcritical regime from one in
Structural holes
Structural holes is a concept from social network research, originally developed by Ronald Stuart Burt. The study of structural holes spans the fields of sociology, economics, and computer science. Bu
Evolving network
Evolving networks are networks that change as a function of time. They are a natural extension of network science since almost all real world networks evolve over time, either by adding or removing no
Network formation
Network formation is an aspect of network science that seeks to model how a network evolves by identifying which factors affect its structure and how these mechanisms operate. Network formation hypoth
Human disease network
A human disease network is a network of human disorders and diseases with reference to their genetic origins or other features. More specifically, it is the map of human disease associations referring
Consumer network
The notion of consumer networks expresses the idea that people's embeddedness in social networks affects their behavior as consumers. Interactions within consumer networks such as information exchange
Network science
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, co
Degree-preserving randomization
Degree Preserving Randomization is a technique used in Network Science that aims to assess whether or not variations observed in a given graph could simply be an artifact of the graph's inherent struc
Hierarchical closeness
Hierarchical closeness (HC) is a structural centrality measure used in network theory or graph theory. It is extended from closeness centrality to rank how centrally located a node is in a directed ne
Fractal dimension on networks
Fractal analysis is useful in the study of complex networks, present in both natural and artificial systems such as computer systems, brain and social networks, allowing further development of the fie
Network on a chip
A network on a chip or network-on-chip (NoC /ˌɛnˌoʊˈsiː/ en-oh-SEE or /nɒk/ knock) is a network-based communications subsystem on an integrated circuit ("microchip"), most typically between modules in
Global cascades model
Global cascades models are a class of models aiming to model large and rare cascades that are triggered by exogenous perturbations which are relatively small compared with the size of the system. The
Evolution of a random network
Evolution of a random network is a dynamical process, usually leading to emergence of giant component accompanied with striking consequences on the network topology. To quantify this process, there is
Collective classification
In network theory, collective classification is the simultaneous prediction of the labels for multiple objects, where each label is predicted using information about the object's observed features, th
Wang algebra
In algebra and network theory, a Wang algebra is a commutative algebra , over a field or (more generally) a commutative unital ring, in which has two additional properties:(Rule i) For all elements x
Hub (network science)
In network science, a hub is a node with a number of links that greatly exceeds the average. Emergence of hubs is a consequence of a scale-free property of networks. While hubs cannot be observed in a
History of network traffic models
Design of robust and reliable networks and network services relies on an understanding of the traffic characteristics of the network. Throughout history, different models of network traffic have been
Narrative network
A narrative network is a system that represents complex event sequences or characters’ interactions as depicted by a narrative text. Network science methodology offers an alternative way of analysing
Exponential family random graph models
Exponential family random graph models (ERGMs) are a family of statistical models for analyzing data from social and other networks. Examples of networks examined using ERGM include knowledge networks
Louvain method
The Louvain method for community detection is a method to extract communities from large networks created by Blondel et al. from the University of Louvain (the source of this method's name). The metho
Network theory
Network theory is the study of graphs as a representation of either symmetric relations or asymmetric relations between discrete objects. In computer science and network science, network theory is a p
Structural cut-off
The structural cut-off is a concept in network science which imposes a degree cut-off in the degree distribution of a finite size network due to structural limitations (such as the simple graph proper
Complex network
In the context of network theory, a complex network is a graph (network) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs but often
Node deletion
Node deletion is the procedure of removing a node from a network, where the node is either chosen randomly or directly. Node deletion is used to test the robustness and the attack tolerance of network
First passage percolation
First passage percolation is a mathematical method used to describe the paths reachable in a random medium within a given amount of time.
LASCNN algorithm
In graph theory, LASCNN is a Localized Algorithm for Segregation of Critical/Non-critical Nodes The algorithm works on the principle of distinguishing between critical and non-critical nodes for netwo
Efficiency (network science)
In network science, the efficiency of a network is a measure of how efficiently it exchanges information and it is also called communication efficiency. The underlying idea (and main assumption) is th
Hyperbolic geometric graph
A hyperbolic geometric graph (HGG) or hyperbolic geometric network (HGN) is a special type of spatial network where (1) latent coordinates of nodes are sprinkled according to a probability density fun
Link analysis
In network theory, link analysis is a data-analysis technique used to evaluate relationships (connections) between nodes. Relationships may be identified among various types of nodes (objects), includ
Global shipping network
The global shipping network is the worldwide network of maritime traffic. From a network science perspective ports represent nodes and routes represent lines. Transportation networks have a crucial ro
Deterministic scale-free network
A scale-free network is a type of networks that is of particular interest of network science. It is characterized by its degree distribution following a power law. While the most widely known generati
Network controllability
Network Controllability is concerned about the structural controllability of a network. Controllability describes our ability to guide a dynamical system from any initial state to any desired final st
Similarity (network science)
Similarity in network analysis occurs when two nodes (or other more elaborate structures) fall in the same equivalence class. There are three fundamental approaches to constructing measures of network
Program evaluation and review technique
The program evaluation and review technique (PERT) is a statistical tool used in project management, which was designed to analyze and represent the tasks involved in completing a given project. First
Weighted network
A weighted network is a network where the ties among nodes have weights assigned to them. A network is a system whose elements are somehow connected. The elements of a system are represented as nodes
Shortest path problem
In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized. The probl
Networks in labor economics
Networks in labor economics refers to the effect social networks have on jobseekers obtaining employment. Research suggests that around half of the employed workforce found their jobs through social c
Average path length
Average path length, or average shortest path length is a concept in network topology that is defined as the average number of steps along the shortest paths for all possible pairs of network nodes. I
Non-linear preferential attachment
In network science, preferential attachment means that nodes of a network tend to connect to those nodes which have more links. If the network is growing and new nodes tend to connect to existing ones
Linear scheduling method
Linear scheduling method (LSM) is a graphical scheduling method focusing on continuous resource utilization in repetitive activities.
Critical path method
The critical path method (CPM), or critical path analysis (CPA), is an algorithm for scheduling a set of project activities. It is commonly used in conjunction with the program evaluation and review t
Network homophily
Network homophily refers to the theory in network science which states that, based on node attributes, similar nodes may be more likely to attach to each other than dissimilar ones. The hypothesis is
NodeXL
NodeXL is a network analysis and visualization software package for Microsoft Excel 2007/2010/2013/2016. The package is similar to other network visualization tools such as Pajek, UCINet, and Gephi. I
Social objects
Social objects are objects that gain meaning through processes of reification (e.g. ritual). Studies of this phenomenon have its origins in classical cognitive sociology, the historical traditions of
Modularity (networks)
Modularity is a measure of the structure of networks or graphs which measures the strength of division of a network into modules (also called groups, clusters or communities). Networks with high modul
Menger's theorem
In the mathematical discipline of graph theory, Menger's theorem says that in a finite graph, the size of a minimum cut set is equal to the maximum number of disjoint paths that can be found between a
Economics of networks
Economics of networks is a discipline in the fields of economics and network sciences. It is primarily concerned with the understanding of economic phenomena by using network concepts and the tools of
Pollination network
A pollination network is a bipartite mutualistic network in which plants and pollinators are the nodes, and the pollination interactions form the links between these nodes. The pollination network is
Clustering coefficient
In graph theory, a clustering coefficient is a measure of the degree to which nodes in a graph tend to cluster together. Evidence suggests that in most real-world networks, and in particular social ne
Assortativity
Assortativity, or assortative mixing is a preference for a network's nodes to attach to others that are similar in some way. Though the specific measure of similarity may vary, network theorists often
Small-world routing
In network theory, small-world routing refers to routing methods for small-world networks. Networks of this type are peculiar in that relatively short paths exist between any two nodes. Determining th
Network scheduler
A network scheduler, also called packet scheduler, queueing discipline (qdisc) or queueing algorithm, is an arbiter on a node in a packet switching communication network. It manages the sequence of ne
Link-centric preferential attachment
In mathematical modeling of social networks, link-centric preferential attachmentis a node's propensity to re-establish links to nodes it has previously been in contact with in time-varying networks.
Rich-club coefficient
The rich-club coefficient is a metric on graphs and networks, designed to measure the extent to which well-connected nodes also connect to each other. Networks which have a relatively high rich-club c
Tribe (internet)
The terms internet tribe or digital tribe are used as slang terms for unofficial online communities or organizations of people who share a common interest, and who are usually loosely affiliated with
Sequence step algorithm
A sequence step algorithm (SQS-AL) is an algorithm implemented in a discrete event simulation system to maximize resource utilization. This is achieved by running through two main nested loops: A sequ