You seem to do a lot of work on sparse graphs, as most people do, but if you re-read the opening line carefully:
> In graph theory, an adjacency matrix is a square matrix used to represent a finite (and usually dense) graph.
Many of these issues evaporate on the realization the article sets out to talk talk to the use of adjacency matrices for dense graphs, which it's trying to point out are the ones you'd commonly use an adjacency matrix for, rather than trying to claim all graphs are dense so you should always use an adjacency matrix.
E.g. a dense graph of 1,000,000 nodes would usually be considered "a pretty damn large dense graph" and so on. These are probably good things to have mentioned here though, as pulling in an article about adjacency matrices for conversation without context of knowing why you're using one already can lead to bad conclusions by folks.
> In graph theory, an adjacency matrix is a square matrix used to represent a finite (and usually dense) graph.
Many of these issues evaporate on the realization the article sets out to talk talk to the use of adjacency matrices for dense graphs, which it's trying to point out are the ones you'd commonly use an adjacency matrix for, rather than trying to claim all graphs are dense so you should always use an adjacency matrix.
E.g. a dense graph of 1,000,000 nodes would usually be considered "a pretty damn large dense graph" and so on. These are probably good things to have mentioned here though, as pulling in an article about adjacency matrices for conversation without context of knowing why you're using one already can lead to bad conclusions by folks.