Figure 2: A scriptcloud, showing 64 tags, based on frequent words retained following application of a stoplist. Produced by an earlier version of Contentcloud,

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www.contentclouds.com, using television program CSI 101.

## 3 Application To Sematics-Based Tag Cloud Visualization 3.1 Television Transcripts

Let us now turn our attention to tag clouds. To start with, we use other implementations of tag clouds as an alternative approach to visualization, for comparison purposes. Then we explore how we can use the Correspondence Analysis opening up the filmscript semantics for us in order to enhance the tag clouds. As we will show tag clouds can express additional information about our filmscript data while still maintaining the very clear display format.

The tag clouds of Figures 2 and 3 use frequency information related to word occurrence, and order words alphabetically. There is nothing in such tag clouds that takes into account the sequential order of the original text. The number of words is set by the user.

Our tag cloud in Figure 4 orders words by scene, where the words are the best characterizations of the scenes, in the sense described in section 2.2. Thus the most important structuring of the original text, viz. the sequence of scenes, is respected by this output display. The number of words is the same as the number of scenes.