[macrolocal]

You might be missing my point somewhat. :)

First, the methods of the paper don’t have to be a Mendelssohn replacement to be useful. Second, if you don’t like that potential application, consider all the other predictive models that could benefit from these features.

[dahart]

And likewise, you might be missing the point. This paper doesn’t really seem to add any useful knowledge to the corpus, and its methods are extremely unlikely to be useful at all for any of the purposes you are suggesting or imagining. We’ve already had gzip for a long time, and we already know it does not make a good predictive model for anything except storage space.

Like I would totally agree that there’s value in predictive models. I just don’t think the work we’re commenting on is one of those, nor headed toward making one.

[macrolocal]

My point is just that proving known facts can be useful and interesting.

As for the paper, network entropy and node heterogeneity seem to be perfectly sensible statistical concepts, and encode useful information. They also dovetail conveniently with powerful tools in machine learning. Criticizing this paper for lack of potential applications feels unreasonable.