Thanks everyone who’s bought a copy of Visualizing with Text. I hope you’re enjoying it.
I’m really appreciate some of the examples I’m seeing in the wild. Here’s some fantastic examples from Georgios Karamanis. I like the shifted + bold text indicating voting topics at the UN, and word-pairs describing makeup. And Georgios provides the code, so if you’re into R and want to see how to implement some of the text visualization techniques from the book, see his github.
Also exciting to see an endorsement from Michael Friendly, and many others on Twitter. Thanks for the posts.
I’ve talked about the book internally at our company (Uncharted) and have been pleasantly surprised to see some of the ideas weaving their way into some of our visual analytics, such as a button indicating the color legend within the button glyph; or a technique for interactively labelling neighbourhoods while zooming around a massive network.
While I can’t really do a book tour during Covid, I did a talk at Naomi Robbins’ Data Visualization NYC Meetup and interview with Lee Feinberg’s Analytic Stories. Looking back at the videos, I see I may have talked over a couple people – sorry! Happy to follow up.
Also, I noticed some Tweets regarding Typograms, or more generally laying out type to fit into shapes such as Aaron Kuehn‘s beautifully typographic anatomical posters. It’s a technique discussed in the book, such as Automatic Typographic Maps, which in turn were based on Axis Maps; Jean-Luc Arnaud‘s typographic maps or Kate McLean‘s smell maps.
This technique of fitting type onto lines or into shapes has been going on for centuries: I like Calligrammes from the early 20th century, medieval monks speaking in scrolls (on the cover of the book!), text set into the shape of an axe in a book from 1530, or awesome psychedelic posters, such as Wes Wilson‘s posters from the 1960’s. For any visualization researchers interested in algorithms for fitting text into complex shapes, see Ron Maharik’s Digital Micrography research and PhD thesis.