Inside the Voynich Network: graph analysis

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Do I think correctly that dimensions and their interpretation in Principal Component Analysis emerge from the used data and so are different each time?

So is the meaning of PCA1 and PCA2 the same on both graphs?

Yes. PCA dimensions always depend on the data you use. This means the patterns that define PCA1 and PCA2 change whenever the values or graph metrics change. So. the interpretation of the components is not fixed. so PCA1 and PCA2 in one analysis will not necessarily mean the same as PCA1 and PCA2 in another.

In fact, it is a good way to summarize and put a whole bunch of results in an easy to see plot, but it is quite difficult to understand the PCA components meaning. That's why I said I have many other plots to check the graph characteristics separately.