我想在我的交易数据网络上计算特征集中度。但是，每次运行igraph中的eigen_centrality函数时，它都会为节点创建不同的结果。
代码如下：
relations <- data.frame(from = data$from,
to = data$to)
network <- graph_from_data_frame(relations, directed = T)
E(network)$weight <- log(data$amount + 1.1) # weight of the edges
V(network)$eigenCentrality <- eigen_centrality(network, scale = TRUE)$vector
network_data <- igraph::as_data_frame(network, what = "vertices")
head(network_data)
上面的代码的结果每次运行都会产生不同的结果。
运行结果：
name eigenCentrality
<chr> <dbl>
5695 5695 0.00000000000000004061352
9379 9379 0.00000000000000001507577
8170 8170 0.00000000000000002865109
9845 9845 0.00000000000000000000000
9640 9640 0.00000000000000000000000
5815 5815 0.00000000000000000000000
另一次运行的结果：
name eigenCentrality
<chr> <dbl>
5695 5695 0.0000000000000000000000
9379 9379 0.0000000000000000000000
8170 8170 0.0000000000000000000000
9845 9845 0.0000000000000002674064
9640 9640 0.0000000000000000000000
5815 5815 0.0000000000000011516567
可能是什么原因造成的？
可复制的示例：
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