![]() “Network Centralization with the Gil Schmidt Power Centrality Index” Social Networks, 29, 81-92. Proceedings of the International Social Network Conference, Charleston, SC, 22-25. “The Origin of the Mexican Network of Power”. “Centrality in Social Networks I: Conceptual Clarification.” Social Networks, 1, 215-239. Judicious use of geodist.precomp can save a great deal of time when computing multiple path-based indices on the same network. This may be obtained via the argument cmode="gil-schmidt".Ī vector, matrix, or list containing the closeness scores (depending on the number and size of the input graphs). The closeness of a vertex v is defined asĬ_C(v) = \frac defined to be 0 for vertices with no outneighbors. Logical should edge values be ignored when calculating geodesics? If true, centrality scores are rescaled such that they sum to 1. String indicating the type of closeness centrality being computed (distances on directed or undirected pairs, or an alternate measure).Ī geodist object precomputed for the graph to be analyzed (optional) diag is FALSE by default.īoolean indicating whether or not the theoretical maximum absolute deviation from the maximum nodal centrality should be returned. The package provides data on countries and their main city or agglomeration and the different distance measures and dummy variables indicating whether two countries are contiguous, share a common language or a colonial relationship. Set this true if and only if the data can contain loops. The goal of geodist is to provide the same data from GeoDist ready to be used in R (i.e. gmode is set to "digraph" by default.īoolean indicating whether or not the diagonal should be treated as valid data. "digraph" indicates that edges should be interpreted as directed "graph" indicates that edges are undirected. String indicating the type of graph being evaluated. List indicating which nodes are to be included in the calculation. Integer indicating the index of the graph for which centralities are to be calculated (or a vector thereof). Tmaxdev=FALSE, cmode="directed", geodist.precomp=NULL, ![]() Usage closeness(dat, g=1, nodes=NULL, gmode="digraph", diag=FALSE, Depending on the specified mode, closeness on directed or undirected geodesics will be returned this function is compatible with centralization, and will return the theoretical maximum absolute deviation (from maximum) conditional on size (which is used by centralization to normalize the observed centralization score). Phylogenetic plots were created using the R packages ggtree, ouch and treeio 11,12,13. The angle AOB formed by A (Shanghai), O (Center of Earth), and B (New York) in the figure below (borrowed from: link, just to give an idea ) is acos(-0.28) = 1.86 radians, or in degrees: 1.86/3.14*180 = 106.6 °.Compute the Closeness Centrality Scores of Network Positions DescriptionĬloseness takes one or more graphs ( dat) and returns the closeness centralities of positions (selected by nodes) within the graphs indicated by g. coordinates with the geodist function in package geodist 10. Usage geodist (dat, inf.replaceInf, count.pathsTRUE, predecessorsFALSE, ignore.evalTRUE, na. Where geodesics do not exist, the value in inf.replace is substituted for the distance in question. = -0.28 -> this output is a value from -1 to 1 Description geodist uses a BFS to find the number and lengths of geodesics between all nodes of dat. The sin and cos functions take latitudes and longitudes input in radians in most softwares. The distance in kilometers is calculated using the Spherical Law of Cosines :ĭ = acos( sin(lat1)*sin(lat2) + cos(lat1)* cos (lat2)* cos (long2-long1) ) * 6371 (km) As well as how the distances between geological points were calculated Calculating the distance between two points on the earth is fundamental to calculate all the measurements mentioned in earlier posts.
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