# analysing node connectivity difference in a continuous scale (edge weighted by correlations)

I have an edge list object weighted by a correlation value. I would like to know the changes in the node's connectivity on a continuous scale.

In other words, how does the node connectivity differ from the edge weight scale (-1) to the edge weight (+1)? I would like to know how to do this or whether any R package or statistical model could solve the problems etc.

I would like to know whether node connectivity increases or decreases in relation to the correlation weight. I.e. how it looks at the correlation between node degree and edge weight. But I don't know how to do it.

A example edge list object is created in the code below.

data <- structure(list(from = c(5L, 5L, 5L, 1L, 1L, 1L, 1L, 4L, 4L, 4L,
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L),
to = c(1L, 2L, 3L, 5L, 4L, 2L, 3L, 1L, 2L, 3L, 5L, 1L, 4L, 3L, 5L, 1L, 4L, 2L),
weight = c(runif(18, -1,1))),
row.names = c(NA, -18L),
class = "data.frame")


I appreciate your help!! Best, Amare

• if I understand correctly, something like, "do nodes with higher UNWEIGHTED degree also tend to have higher weight on their edges?" Jan 25 at 0:47