betweenness(sna)
betweenness()所属R语言包：sna
Compute the Betweenness Centrality Scores of Network Positions
计算中间中心得分的网络位置
译者：生物统计家园网 机器人LoveR
描述----------Description----------
betweenness takes one or more graphs (dat) and returns the betweenness centralities of positions (selected by nodes) within the graphs indicated by g. Depending on the specified mode, betweenness 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).
betweenness需要一个或多个图形（dat）和返回“中间的位置（选择nodes）内的图形的中心性g。根据指定的模式，中介向或无向的测地线，将返回此功能是兼容centralization，将返回的理论最大绝对偏差（最大）有条件的大小（它是由<X >标准化集中观察到的得分）。
用法----------Usage----------
betweenness(dat, g=1, nodes=NULL, gmode="digraph", diag=FALSE,
tmaxdev=FALSE, cmode="directed", geodist.precomp=NULL,
rescale=FALSE, ignore.eval=TRUE)
参数----------Arguments----------
参数：dat
one or more input graphs.
一个或多个输入图表。
参数：g
integer indicating the index of the graph for which centralities are to be calculated (or a vector thereof). By default, g=1.
整数，指示其中中心性计为（或它们的向量）的曲线图的索引。默认情况下，g= 1。
参数：nodes
vector indicating which nodes are to be included in the calculation. By default, all nodes are included.
矢量的指示哪些节点要被包括在计算中。默认情况下，所有的节点都包括在内。
参数：gmode
string indicating the type of graph being evaluated. "digraph" indicates that edges should be interpreted as directed; "graph" indicates that edges are undirected. gmode is set to "digraph" by default.
的图表类型的字符串，表示正在评估中。表明边缘应被解释为指示“有向图”，“图形”表明边缘是无向。 gmode设置为默认情况下，“有向图”。
参数：diag
boolean indicating whether or not the diagonal should be treated as valid data. Set this true if and only if the data can contain loops. diag is FALSE by default.
布尔值，表示是否对角线应被视为有效的数据。设置这是真的，当且仅当数据可以包含循环。 diag是FALSE默认情况下。
参数：tmaxdev
boolean indicating whether or not the theoretical maximum absolute deviation from the maximum nodal centrality should be returned. By default, tmaxdev==FALSE.
布尔值，表示是否从最大的节点的中心性的理论最大绝对偏差应返回。默认情况下，tmaxdev==FALSE。
参数：cmode
string indicating the type of betweenness centrality being computed (directed or undirected geodesics, or a variant form – see below).
字符串表示的类型的中介中心计算（有向或无向图的测地线，或变体形式 - 见下文）。
参数：geodist.precomp
A geodist object precomputed for the graph to be analyzed (optional)
Ageodist对象的预计算的图形进行分析（可选）
参数：rescale
if true, centrality scores are rescaled such that they sum to 1.
如果为true，中心的分数重新调整，他们总结到1。
参数：ignore.eval
logical; ignore edge values when computing shortest paths?
逻辑，忽略边缘值时，计算最短路径？
Details
详细信息----------Details----------
The shortest-path betweenness of a vertex, v, is given by
介的顶点的最短路径，v，是由
C_B(v) = sum( g_ivj / g_ij, i,j: i!=j,i!=v,j!=v )</i>
C_B（V）=的总和（g_ivj / g_ij，I，J：我！= j时，我！= V，J = V）</ I>
where g_ijk is the number of geodesics from i to k through j. Conceptually, high-betweenness vertices lie on a large number of non-redundant shortest paths between other vertices; they can thus be thought of as “bridges” or “boundary spanners.”
g_ijk是i到k通过j数测地线。从概念上讲，高介顶点趴在大量的非冗余的其他顶点之间的最短路径，因此他们可以被认为是“桥梁”或“边界扳手。”
Several variant forms of shortest-path betweenness exist, and can be selected using the cmode argument. Supported options are as follows:
存在几种不同形式的最短路径介，可以选择使用cmode参数。支持的选项如下：
directed Standard betweenness (see above), calculated on directed pairs. (This is the default option.)
undirected Standard betweenness (as above), calculated on undirected pairs (undirected graphs only).
undirected标准介（如上图），计算无向双（仅适用于无向图）。
endpoints Standard betweenness, with direct connections counted towards ego's score. This expresses the intuition that individuals' control over their own direct contacts should be considered in their total score (e.g., when betweenness is interpreted as a measure of information control).
endpoints的标准介，与自我的得分计入直接连接。这表示直觉，个人控制自己的直接接触，应考虑他们的总成绩（例如，当介解释作为衡量信息控制）。
proximalsrc Borgatti's proximal source betweenness, given by
的proximalsrc的博尔加蒂的近源介，
C_B(v) = sum( g_ivj / g_ij, i,j: i!=v,i!=j,j->v ).</i>
C_B（V）= SUM（g_ivj / g_ij，I，J：我= V，I！= J，J-V）。</ I>
C_B(v) = sum( g_ivj / g_ij, i,j: i!=j,i->v,j!=v ).</i>
C_B（V）=的总和（g_ivj / g_ij，I，J：我！= j时，我 - > V，J = V）。</ I>
C_B(v) = sum( (1/d_ij)*(g_ivj / g_ij), i,j: i!=j,i!=v,j!=v ),</i>
C_B（V）= SUM（（1/d_ij）*（g_ivj / g_ij），I，J：我= j时，我= V，J = V），</ I>
C_B(v) = sum( (d_iv/d_ij)*(g_ivj / g_ij), i,j: i!=j,i!=v,j!=v ).</i>
C_B（V）= SUM（（d_iv / d_ij）*（g_ivj / g_ij），I，J：我= j时，我= V，J = V）。</ I>
值----------Value----------
A vector, matrix, or list containing the betweenness scores (depending on the number and size of the input graphs).
包含“中间分数（取决于上的输入图形的数量和大小）的向量，矩阵，或列表。
警告----------Warning ----------
Rescale may cause unexpected results if all actors have zero betweenness.
重缩放可能会导致意外的结果，如果所有的演员都为零介。
注意----------Note----------
Judicious use of geodist.precomp can save a great deal of time when computing multiple path-based indices on the same network.
明智地使用geodist.precomp计算时，可以节省大量的时间在同一网络上的多个路径为基础的指数。
（作者）----------Author(s)----------
Carter T. Butts <a href="mailto:buttsc@uci.edu">buttsc@uci.edu</a>
参考文献----------References----------
Borgatti, S.P. and Everett, M.G. (2006). “A Graph-Theoretic Perspective on Centrality.” Social Networks, 28, 466-484.
Brandes, U. (2008). “On Variants of Shortest-Path Betweenness Centrality and their Generic Computation.” Social Networks, 30, 136–145.
Freeman, L.C. (1979). “Centrality in Social Networks I: Conceptual Clarification.” Social Networks, 1, 215-239.
Geisberger, R., Sanders, P., and Schultes, D. (2008). “Better Approximation of Betweenness Centrality.” In Proceedings of the 10th Workshop on Algorithm Engineering and Experimentation (ALENEX'08), 90-100. SIAM.
参见----------See Also----------
centralization, stresscent, geodist
centralization，stresscent，geodist
实例----------Examples----------
g<-rgraph(10) #Draw a random graph with 10 members[绘制一个随机的10名成员组成的图，]
betweenness(g) #Compute betweenness scores[计算介得分]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 10:48:08
