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+--- Thread: Relation between word types and vocabulary density. (/thread-6244.html)
Relation between word types and vocabulary density. - Koen G - 25-10-2026
There have been interesting discussions lately about @npcompl33t's seriation research. Admittedly, some of that is over my head, since my brain prefers things that are more concr33t. Some of the graphs reminded me quite a bit of my MATTR research. This is a while ago (2019) so I went digging in my notes, and used Claude to make some new graphs. Marco has been kind enough to explain some things that weren't clear to me yet and to suggest some improvements.
In my attempt to vulgarize the discourse, which is another purpose of this thread, I will no doubt introduce inaccuracies, so please do correct me if I'm wrong.
Let me first illustrate how Davis & Layfield's and npcompl33t's seriations reminded me of things I had seen before:
I will try to explain in my own words what I think is happening here. If we assume bifolios are sequential and not supposed to be nested (singulions vs quire structure), then three seemingly different approaches point to the same order.
- Davis & Layfield look at which words occur together. The technique they used, LSA, works at the word level and is interested in what kinds of words can be used to order folios. They remove the most common words, and then find connections between folios based on shared specific vocabulary.
- npcompl33t's technique does not consider whole words at all, but only looks at which glyphs tend to follow each other. Pages that use glyph pairs in similar proportions sit close together.
- MATTR looks at TTR, type-token ratio. It expresses how rich the vocabulary of a given text is, without caring about the specifics. You simply divide the number of different words (types) by the total word count (tokens). The higher the number, the richer the vocabulary.
All three seemingly different things lead to the same proposed bifolio order. This next graph compares MATTR to npcompl33t's MDS1, which is the main "line" of his analysis. You can think of this as the strongest way to spread out all folios based on their preferred glyph pairs. It basically sorts folios according to Currier A - B, since it focuses on the low-hanging fruit: prevalence of edy-type words typical for Currier B, and cho-type words.
What we observe is that the more extreme B-folios (left) and the more extreme A-folios (right) also have the lowest vocabulary density. No doubt, all of these stats are related. If a page is more repetitive, this is felt in its "core" word types. Or the other way around, if a page falls back more on its more typical A vs B word types, it also becomes more repetitive.
I personally remain skeptical of the viability of seriation based on so little text, but that is another discussion. What does stand out for me here is that we can see some very clear divisions between and within sections.
- Q13 stands out due to its relatively low density of vocabulary. You can see it all the way at the bottom of the graph. Some Q13 folios are notably worse than others.
- Q20 splits very clearly. Two bifolios are almost as poor in vocabulary as Q13, and three bifolios are among the richest in the MS. But it all takes place on the B-side.
- There is a lot of variability within Herbal A, but this may be due to its limited amount of text per page.
- Some pages are strong outliers. What is even going on with f33/f40? Interestingly, the closely bound f34-f39 shows the largest distance between folios that are on the same sheet.
- The two folios of Q8, especially 58-65, are near the middle on the MDS1, which is no surprise since Q8 is an inconsistent mess, distant from typical A and B.
RE: Relation between word types and vocabulary density. - nablator - 25-10-2026
RE: Relation between word types and vocabulary density. - Koen G - 25-10-2026