Textour is an interactive tool that allows the analysis of a large body of text through a radial convergence visualization. As Tim Walter explains: "I got inspired to develop this application as my diploma project because the digitalization of media and the internet make many texts on the internet easily accessible to everyone; written literature on the other hand is mostly not accessible on the internet. As a consequence, there is a need to access this information via the same digital tools (...) I therefore dealt with the big market of text mining; as an information designer I wanted to think about the appearance of text in general and a new way to visualize a text for different purposes."
Due to the fact that every text is more or less carefully articulated, speeches but also narrative and law texts make language a very complex subject that is difficult to analyze properly. Nevertheless, it is possible to discover certain rules which show that every text is a system of words where length, position and frequency do not appear at random. In Textour, Tim Walter integrated some basic filters (text restriction, sentence restriction, word restriction, sentence length, word length, word frequency) to discover keywords and text patterns. The key advantage of these basic filters is that they work automatically and are flexible enough to be transferred to other languages.
Here is how Tim describes the method used on this visualization: "First of all I split the text into the different sentences, words and letters and then I re-connected them to the corresponding lines. After that I arranged the different text elements, letters, words and sentences on three different circles around a common center. (...) Every time a letter, word or sentence is entered into the program, the visualisation integrates the new item and the elements appear on the right point of intersection of line through the center and the circles and re-arranges the rest of the elements in a clockwise manner. The different colours in the visualization represent every single word and are attributed to the word the first time the word appears, they also show when a word appeared for the first time and how often it was found in the whole text".