This is a visualization tool that allows for analyzing changes in ranked and (if desired) valued lists over time. To try it out, download this file and paste the first 15 row or so (including the first row) from Excel into the textarea below. This file contains the top ranked videos on YouTube for the query "syria" on five consecutive days, as well as the viewcount for each video. Use the logarithm checkbox for better display.

You can either use data that is merely a collection of ranked items (tab separated single columns, example) or combinations of items and a value (tab separated list of two columns, example).

This tool also calculates the Rank-Biased Distance (RBD) metric to quantify changes from one slice to the next. The higher the RBD value, the more change. The "RBD p" parameter (value is between 0.01 and 0.99) below allows to determine how "top-weighed" the calculation should be. With a small p, changes at the top of the lists are weighed more strongly, with p approaching 1 all changes are treated the same. Calculations are based on William Webber, Alistair Moffat, and Justin Zobel (2010) "A similarity measure for indefinite rankings." ACM Transactions on Information Systems 28(4), 20. (ACM library / preprint)

The source code of this tool is available here.

make uservariable logarithmic for bar height calculation (useful if the differences between smallest and greatest value are very big, ignored in single column mode)

use inverse rank for bar size in single column mode (ignored in two column mode)

shorten labels (if text is too long)

width: / height:

RBD p: