{"id":16173,"date":"2023-01-19T23:15:47","date_gmt":"2023-01-19T23:15:47","guid":{"rendered":"https:\/\/www.anychart.com\/blog\/?p=16173"},"modified":"2023-03-02T16:05:12","modified_gmt":"2023-03-02T16:05:12","slug":"visualizing-text-data-hierarchy","status":"publish","type":"post","link":"https:\/\/www.anychart.com\/blog\/2023\/01\/19\/visualizing-text-data-hierarchy\/","title":{"rendered":"Visualizing Text Data Hierarchy with Word Trees"},"content":{"rendered":"

\"Visualizing<\/a>Over the past few weeks, I have been looking for a quick and effective way of representing the structural differences within a set of similar-looking short sentences.<\/p>\n

To provide a bit of context, as we approached the end of 2022, my workmates and I got heavily involved in a planning phase for the new year to start. More specifically, we were asked to write a set of objectives<\/em> and key results<\/em> that would help drive a common strategy across our supported programs and pillars over the months to come.<\/p>\n

And as expected, each and every one of us ended up leaving comments for every subtle change made to the couple of sentences that had initially been dropped into a shared document. As the comments started piling up, it quickly became quite tedious to follow and understand the slight modifications that were being made to our original set of objectives<\/em> and key results<\/em>.<\/p>\n

As I started exploring what we could have done to better capture and visualise these changes, I recently found a way to display text data in a hierarchical way that I thought would be worth sharing.<\/p>\n

<\/p>\n

Spot the differences<\/h2>\n

Let\u2019s start by creating some textual data that we\u2019ll be using throughout this article as a basis for our word tree charts:<\/p>\n

\"Julien is a big fan of pizzas and salted caramel\"\r\n\"Julien loves pizzas and salted caramel\"\r\n\"Julien is a big fan of food in general\"\r\n\"Julien loves pizzas but he hates onions\"\r\n\"Julien is a big fan of pizzas but he hates onions\"\r\n\"Julien is a big fan of pizzas but he absolutely hates onions\"\r\n\"Julien is a big fan of pizzas\"\r\n\"Julien loves pizzas\"<\/code><\/pre>\n
What we can immediately tell is that though the above sentences look quite similar, they are yet slightly different. The fact that we\u2019re only dealing with a handful of strings probably helps us visualise their syntaxic nuances.<\/p>\n
But I\u2019m wondering what would happen if we had 50 times as many sentences. Would we still be able to easily spot how different they are?<\/p>\n
Now, a sensible approach to that dimensionality problem would be to rely on either of the following string distance metrics:<\/p>\n