Posts with tag Dunning
Back to all postsI may (or may not) be about to dash off a string of corpus-comparison posts to follow up the ones I’ve been making the last month. On the surface, I think, this comes across as less interesting than some other possible topics. So I want to explain why I think this matters now. This is not quite my long-promised topic-modeling post, but getting closer.
As promised, some quick thoughts broken off my post on Dunning Log-likelihood. There, I looked at _big_ corpuses–two history classes of about 20,000 books each. But I also wonder how we can use algorithmic comparison on a much smaller scale: particularly, at the level of individual authors or works. English dept. digital humanists tend to rely on small sets of well curated, TEI texts, but even the ugly wilds of machine OCR might be able to offer them some insights. (Sidenote–interesting post by Ted Underwood today on the mechanics of creating a middle group between these two poles).
Historians often hope that digitized texts will enable better, faster comparisons of groups of texts. Now that at least the 1grams on Bookworm are running pretty smoothly, I want to start to lay the groundwork for using corpus comparisons to look at words in a big digital library. For the algorithmically minded: this post should act as a somewhat idiosyncratic approach to Dunning’s Log-likelihood statistic. For the hermeneutically minded: this post should explain why you might need _any_ log-likelihood statistic.