# Analyze mixture of data attributes

When I have a list of persons (nodes) with the attributes:

I can search for the people with most links and the people with most revenue. But when I want to know who has the highest "mixture" of both attribues: How can I do this?

That is: We have a ramdon variable $X_1$ for revenue and a random variable $X_2$ for links. I can order the data $\hat{X_1}$ and I can order the data $\hat{X_2}$. But I do not know how to order the list $(\hat{X_1}|\hat{X_2})$.

I have read that the Principal component analysis can be helpful, that is to say, that one can work with eigenvalues etc. to obtain a result. Nonetheless I do not know which steps I would need to follow.

I am new in that area and would like to know which is the best model for that purpose.

given two points $\vec p,\vec q$ in the plane $\mathbb{R}^2$, is there a way of deciding which one is greater or equal then the other? The answer is tricky.
Formally, there is no way of defining a relation such that $\vec p$ is either $>$, $=$ or $<$ then $\vec q$.
But this is not a new problem. Despite this fact, what is commonly done to solve this kind of issues is to exploit functions like norms and say that $\vec p$ is 'bigger' than $\vec q$ if $||\vec p||_2\geq||\vec q||_2$.
Other example of function like the Euclidean norm above might be: $$f(\vec p)=p_1+\alpha\cdot p_2$$