MakingFunctions for constructing, simulating, and importing one-mode and two-mode networks: |
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Make networks with defined structures |
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Make networks with a stochastic element |
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Make networks from/to external formats |
ManipulationFunctions for coercing objects between different classes, reformatting or transforming the type of network, or adding information to or retrieving information from the network. |
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Coercion between migraph-compatible object classes |
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Tools for reformatting networks, graphs, and matrices |
Tools for splitting networks, graphs, and matrices |
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Tools for transforming networks, graphs, and matrices |
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Adding and copying attributes from one graph to another |
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Grab various node or edge attributes from a network |
MarksFunctions for identifying properties of graphs, nodes or ties, all returning logical scalars or vectors. Note that all |
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Marking networks based on their properties |
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Marking nodes based on their properties |
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Marking ties based on their properties |
MeasuresFunctions for measuring multimodal networks, all returning numeric scalars or vectors. Note that all |
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Measures of network cohesion or connectedness |
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Measures of node centrality |
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Measures of tie centrality |
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Measures of network centralisation |
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Measures of network closure |
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Measures of structural holes |
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Measures of network diversity |
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Measures of network topological features |
MotifsFunctions for calculating subgraphs in multimodal networks. These functions have an additional dimension than |
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Censuses of brokerage motifs |
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Censuses of motifs at the network level |
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Censuses of nodes' motifs |
MembershipsFunctions for identifying community, cluster, or class memberships in partitions within multimodal networks. They return integer vectors the length of the nodes in the network. |
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Community graph partitioning algorithms |
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Component partitioning algorithms |
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Equivalence clustering algorithms |
Core-periphery clustering algorithms |
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ModelsFunctions for modelling multimodal networks: |
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Conditional uniform graph and permutation tests |
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Linear and logistic regression for network data |
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Functions to play games on networks |
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Methods for equivalence clustering |
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MappingFunctions for plotting and visualising graphs of different types: |
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Quickly graph networks with sensible defaults |
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Layouts for snapping layouts to a grid |
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Layout algorithms based on bi- or other partitions |
Plot lineage graph |
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Plot the evolution of a network |
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DataThe package contains two collections of multimodal, multilevel, and multiplex network data, including data used in the book Multimodal Political Networks (prefixed with |
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Multimodal (3) Bristol protest events, 1990-2002 (Diani and Bison 2004) |
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One-mode interstate trade relations and two-mode state membership in IGOs (COW) |
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One-mode Mexican power elite database (Knoke 1990) |
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Two-mode and three-mode American power elite database (Domhoff 2016) |
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Two-mode European Values Survey, 1990 and 2008 (EVS 2020) |
One-mode EU policy influence network, June 2004 (Christopoulos 2006) |
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Two-mode 112th Congress Senate Voting (Knoke et al. 2021) |
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One-mode subset (8 individuals) of the adolescent society (Coleman 1961). |
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Multiplex graph object of friends, social, and task ties (McFarland 2001) |
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One-mode and two-mode centrality demonstration networks |
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One-mode karateka network (Zachary 1977) |
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One-mode interaction network of Lord of the Rings (book) character interactions |
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Multilevel two-mode affiliation, signed one-mode networks of Marvel comic book characters (Yüksel 2017) |
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One-mode EIES dataset (Freeman and Freeman 1979) |
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Two-mode projection examples (Hollway 2021) |
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Two-mode southern women (Davis, Gardner and Gardner 1941) |