In italic, here's Mimno's introduction, with a bit chopped out.
This page shows the 500 topics used by Matt Jockers in his book Macroanalysis, which he extracted automatically from ~3000 mostly 19th century English-language novels. The algorithm divided the content of the novels into themes based on word co-occurrence patterns within 1000-word chunks.
Each 1000-word chunk is assigned to one of 20 equal-sized sections. (Long books will have 20 long sections, shorter books will have 20 shorter sections.) A topic that occurs more in early sections of novels will have a decreasing line, like school, while a topic that occurs in later sections will have a rising line, like punishment. The topics are sorted so that topics that occur early in novel time are at the top of the page, and topics that occur late are at the bottom. The gray shaded region represents one standard deviation on either side of the mean — there's a lot of variability between novels.
Unlike Mimno's version, you have to click to see the labels for the mini plots since I'm embedding them in a two dimensional space. You have to click on the plot to make it disappear, since that was easier for me to code.I apologize for the lack of x and y axes on the overall thing--the pearson range for the x axis is -.98 to -.96, and for the y axis -.68 to .86. This was a train-ride project, and I'm pulling into South Station now.