Abstract-We introduce the Word Tree, a new visualization and information-retrieval technique aimed at text documents. A word tree is a graphical version of the traditional "keyword-in-context" method, and enables rapid querying and exploration of bodies of text. In this paper we describe the design of the technique, along with some of the technical issues that arise in its implementation. In addition, we discuss the results of several months of public deployment of word trees on Many Eyes, which provides a window onto the ways in which users obtain value from the visualization. Index Terms-Text visualization, document visualization, Many Eyes, case study, concordance, information retrieval, search. In James Joyce's A Portrait of the Artist as a Young Man, the word "his" appears 1,744 times. The word "her" occurs 316 times. These numbers provide little insight beyond a basic imbalance. Now consider that the most common word to follow "his" is "soul," while the most common word to follow "her" is "eyes." With this fact, the nature of the imbalance begins to emerge. Repeated elements tell us a great deal about texts-but with context more nuances and revealing themes appear. Furthermore, the set of contextual elements often itself has a complex structure. "His soul" appears 83 times in A Portrait of the Artist as a Young Man, but what follows those two words? Among other phrases, "was fattening," "was festering," and "was foul"-along with "was waking," "was enriched," and "was soaring." In this paper we introduce a new visualization technique, the word tree, that makes it easy to explore this type of repetitive context. A word tree places a tree structure onto the words that follow a particular search term, and uses that structure to arrange those words spatially. Simple interaction techniques allow the viewer to examine the ways that a particular word or phrase is used in a text, seeing broad patterns and drilling down into details. The motivation for creating the word tree comes from our experience with user-generated visualizations on the Many Eyes site [11] , which allows anyone to upload and visualize data. Since the site launched in the beginning of 2007, we have observed a growing number of attempts to visualize unstructured text. The first text visualization on the site was a tag cloud-a common technique showing word frequency. Despite the tag cloud's popularity, comments from users indicated they were sometimes as interested in usage context as raw frequency counts. The feedback prompted us to consider a technique that would retain more of the text composition for exploration. The word tree was first made public in September 2007 and, as of March 2008, people have used the word tree to examine more than 650 texts. Because all activity on Many Eyes is public, and because many of its members write about their experiences on blogs, we have a rich record of word tree usage. We take advantage of this record to assess the word tree technique and examine the types of value that it is providing. We also describe feedback from users, which points to several promising research directions. Finding ways to display and refine search results is a classic challenge in information retrieval. The problem predates computers; for centuries biblical scholars have used concordances 1 to see how different words occur in religious texts. The computer-age equivalent of these paper concordances is the "keyword in context" (KWIC) technique [5] , in which hits are shown with the search term, or keyword, surrounded by a snippet of the text in which it occurs. Although these snippets are often arranged so that the keywords are aligned, it can be difficult to see patterns and connections in the resulting array of text. Several visualization methods have been proposed to show word usage. Tilebars [8] provide a compressed overview of search term distribution within a document; the SeeSoft program [4] provides graphical highlighting of textual metadata. The TextArc technique [13] shows the overall distribution of every word in a piece of text. None of these, however, provides an easy way to see the different contexts in which a given word or phrase is used. Other text visualizations, such as dotplots [7] and arc diagrams [14] , spotlight global patterns of repetition but do not provide a detailed view of the context of usage of particular terms. One clever technique for displaying contextual information about a search term is the "star diagram" of Bowdidge and Griswold [2] . Designed to help developers restructure code, a star diagram shows how a particular variable is used in a program. The display uses a tree structure to display which functions are applied to that variable, which functions call those functions, and so forth up the call stack. While it is not directly applicable to plain text, the star diagram's hierarchical arrangement of context makes it a precursor to the work we describe below. As we discuss in the next section, we propose to show context using an interactive tree structure, in which users can click on nodes to vary the level of detail. Three systems directly relate to the interaction techniques we employ. The network exploration program described in Yee et al. [15], the SpaceTree visualization [6] , and Degree-of-Interest Trees (DOITrees) [9] use elegant animations to help users navigate, a design choice that we emulate. The SpaceTree and DOITrees, like our visualization, allow users to easily move up and down a hierarchy. On the other hand, our design for showing levels of detail and handling high branching factors contrasts with SpaceTree and DOITrees, and we discuss some differences in user reaction to this point. 1 The word "concordance" is sometimes used to mean a comparison between texts. In this paper, however, we use it in the literary sense of an index that provides additional context for word usage. • Martin Wattenberg is with IBM Research, E-Mail: mwatten@us.ibm.com. • Fernanda B. Viégas is with IBM Research., E-Mail: viegasf@us.ibm.com.
One of the approaches for supporting text analysis is the representation of a given text as a word tree REF .
The Word Tree, an Interactive Visual Concordance
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Computer Science Medicine