Word trees use a visual branching structure to show how a pre-selected word(s) is connected to other words.
Unlike word clouds, word trees visually display the connection of words in the dataset, providing some context to their use. Words that show up more frequently in combination with the pre-selected word(s) are displayed in larger font sizes. The visualisation allows users to choose whether they are interested in connections preceding a word or following a word. While there are many free web applications for word clouds, word tree applications are limited.
Word tree using Many Eyes
The following two examples show word trees created using Many Eyes (an IBM initiative that has now been discontinued). The text is from interview transcripts of individuals discussing their experience with homelessness.
The first displays words that follow “dignity,” whereas the second shows words that precede it. Sisters of the Road (2002)
Advice for choosing this method
Word trees are most useful in exploratory analysis when an evaluator would like to examine the various ways that a pre-determined word(s) was used in the text. If after conducting early analysis, patterns emerge, word trees might also be used to visually display those patterns in the reporting stage.
Advice for using this method
Because of their text-heavy display, word trees are usually better suited for visual analysis than for reporting to external audiences.
Sisters of the Road (2002) Voices of Homelessness: a qualitative database from sisters of the road. Retrieved April 10, 2013, from http://www.sistersoftheroad.org/voices (archived link)
Wattneberg, M. & Viegas, F. B. (2008). The word tree, an interactive visual concordance. InfoVis. http://hint.fm/papers/wordtree_final2.pdf
'Word tree' is referenced in:
- Rainbow Framework :