映射博客之间的链接连接的最佳方式是什么？

发布于 2024-08-18 12:27:43 字数 86 浏览 10 评论 0原文

我希望对一堆博客进行社交网络分析，绘制谁链接到谁（不仅通过他们的博客，还通过他们的帖子）。什么软件可以执行这样的爬行/数据收集/映射？

谢谢！

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祁梦 2024-08-25 12:27:43

通过“映射”，我不确定您是指将原始数据映射到正统的图形数据结构，还是将该数据结构映射到美学库以进行渲染。如果是前者，那么我猜想编写一个函数将原始数据（w/r/t哪些博客链接到哪个博客以及链接多少）转换成图形数据结构（例如邻接矩阵）是一个简单的问题。映射这样的数据结构以供查看可以如下完成：

library(Rgraphviz)
# create an synthetic adjacency matrix for 10 blogs
M = sapply(rep(10, 10), function(x){sample(c(0, 1), 10, T, c(0.7, 0.3))})
colnames(M) = paste(rep("b", 10), 1:10, sep="-")
rownames(M) = colnames(M) 
# 0's down the main diagonal (eliminate self-edges)
diag(M) = rep(0, 10)
# call the graphviz constructor, passing in adjacency matrix
M_gr = new("graphAM", adjMat=M, edgemode="directed")
g1 = layoutGraph(M_gr)
# (optional) aesthetic parameters for nodes & edges
graph.par( list(edges = list(col="gray", lty="dashed", lwd=1), 
            nodes = list( col="midnightblue", shape="ellipse", 
               textCol="darkred", fill="#B0B7C6", fontsize=11, 
               lty="dotted", lwd=2)) )
# call the device driver
png(file='somefilename.png', width=600, height=460, res=128)
# call the plot function
renderGraph(g1)
# kill the device
dev.off()

alt text http://img13 .imageshack.us/img13/7683/bloggraph.png

如果您不仅想显示连接，还想显示这些连接的强度，例如来自一个博客的链接数量或频率对于另一个，您可以通过参数“lwd”单独设置线条粗细，在本例中，我将所有边缘设置为 2（另一个选项是按线条类型显示连接强度，例如，点线、虚线、实线、颜色）。当然，这些边权重必须在邻接矩阵中设置，这很简单——您可能需要使用“0”，而不是用“0”/“1”来表示“未连接”/“已连接” /'整数'。

By "mapping" I'm not sure if you are referring to mapping of raw data to an orthodox graph data structure or mapping of that data structure to an aesthetics library in order to render it. If the former, then i would guess it's a straightforward matter of writing a function to translate raw data (w/r/t which blogs link to which, and how much) into a graph data structure, such as an adjacency matrix. Mapping such a data structure for viewing can be done like this:

library(Rgraphviz)
# create an synthetic adjacency matrix for 10 blogs
M = sapply(rep(10, 10), function(x){sample(c(0, 1), 10, T, c(0.7, 0.3))})
colnames(M) = paste(rep("b", 10), 1:10, sep="-")
rownames(M) = colnames(M) 
# 0's down the main diagonal (eliminate self-edges)
diag(M) = rep(0, 10)
# call the graphviz constructor, passing in adjacency matrix
M_gr = new("graphAM", adjMat=M, edgemode="directed")
g1 = layoutGraph(M_gr)
# (optional) aesthetic parameters for nodes & edges
graph.par( list(edges = list(col="gray", lty="dashed", lwd=1), 
            nodes = list( col="midnightblue", shape="ellipse", 
               textCol="darkred", fill="#B0B7C6", fontsize=11, 
               lty="dotted", lwd=2)) )
# call the device driver
png(file='somefilename.png', width=600, height=460, res=128)
# call the plot function
renderGraph(g1)
# kill the device
dev.off()

alt text http://img13.imageshack.us/img13/7683/bloggraph.png

If you want to show not just connections but the strength of those connections, e.g., number, or perhaps frequency of links from one blog to another, you can do that by setting line thickness individually, through the parameter 'lwd', which i've set at 2 for all edges, for this example (another option is to show connection strength by line type, e.g., dotted, dashed, solid, color). Of course, these edge weights will have to be set in your adjacency matrix, which is simple enough--instead of '0'/'1' to represent 'not connected'/connected, you'll probably want to use '0'/'integers'.

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