Figure 2

Example allotaxonograph using rank-turbulence divergence (RTD) to compare word usage on two different days of English Twitter. We explain rank-turbulence divergence allotaxonographs in full in Sect. 3.1, providing a summary within this caption. To help with understanding, we again examine the same dates of the 2016 US Presidential Election and the Charlottesville Unite the Right rally as the rank-rank histogram of Fig. 1. We add rank-turbulence divergence to Fig. 1’s histogram with A. A gauge for α and the expression for \(D^{\mathrm{R}}_{1/3}\) in the upper left corner; B. An overlay of contour lines; C. A scale for the contour lines in the upper right; and D. Based on contributions of each word to \(D^{\mathrm{R}}_{1/3}\), an ordered list on the right by descending values of \(\delta D^{\mathrm{R}}_{1/3,\tau }\). In the ordered list, words are arranged left and right and colored gray and blue in accordance with the date on which they are most prevalent. The two dates’ ranks for each word in the list are indicated on the opposite side. For example, \(r_{\mathrm{Trump},1}=11\) and \(r_{\mathrm{Trump},2}=60\), and \(r_{\mathrm{Heyer},1}=862{,}482\) and \(r_{\mathrm{Heyer},2}=445\). While an exact match is intended, a few annotated words on the histogram differ from Fig. 1 due to chance during the automatic annotation of the histogram (e.g., ‘HURRICANE’ on the left side in Fig. 1, but ‘BRITAIN’ here). The instrument’s function and layout are highly configurable in our figure-building script. For example, the choice of divergence (rank or otherwise), axis limits, maximum length of type names, histogram cell size, and the guide adornments ‘less talked about’ and ‘more talked about’ are all system-specific settings. As a design choice, we limit the resolution of α to multiples of 1/12, For full details of the underlying histogram, see the caption of Fig. 1 and Sect. 2.2