for a set of terms.

The χ 2 distance is an appropriate distance for use with such data (Benz´ecri 1979; Murtagh 2005). The χ 2 distance is a weighted Euclidean distance. Consider texts i and i 0crossed by words j. Let kij be the number of occurrences of word j in text i. Then, omitting a constant, the χ 2 distance between texts i and i 0is given by Pj 1/kj (kij/ki − ki 0j/ki 0 )
2. The weighting term here is 1/kj . The weighted Euclidean distance is between the *profile* of text i, viz. kij/ki for all j, and the analogous *profile* of text i 0. Our discussion is to within a constant because we actually work on *frequencies* defined from the numbers of occurrences.

Define fij = kij/k where k =Pi Pj kij . Then the profile of scene i is the set of values fij for all j. Similarly the profile of word j is the set of values fij for all i. We say that fi =Pj fij is the *mass* of scene i; and fj =Pi fij is the mass of word j.

Correspondence Analysis allows us to project the space of texts (we could equally well explore the terms in the *same* projected space) into a Euclidean space. In doing so, Correspondence Analysis transforms (by a linear transform determined from a singular value decomposition) each pairwise χ 2 distance into the corresponding pairwise Euclidean distance.

The Euclidean embedding is good for visualization, given that it is an intuitive one. It is good for static context, including processing of a historical or otherwise sequenced set of information items. All inter-relationships are at once taken into consideration. Furthermore all such inter-relationships together provide context, relativities, and hence meaning. In this sense therefore, Correspondence Analysis is an ideal platform for analysis of semantics (Murtagh, 2009).

## 1.5 Television Filmscripts Used

Production for television is often carried out by multiple teams. Notwithstanding this, there has to be a relatively very formulaic approach adopted to story and personalities. Our goal is to see where and how tag clouds can express well the content of filmscript data. How can tag clouds provide us with a summary of the story and perhaps be displayed in conjunction with other forms of the story such as the movie itself? We seek a better summary than just pure word counts. After all, there is increasingly fast moving convergence in the sector, with successful television series being ported to a games environment (this is the case for CSI); social network content being taken to a television environment
(e.g. Sofia's Diary, www.bebo.com/sofiasdiary); and so on.

In this work we took three CSI (Crime Scene Investigation, Las Vegas –
Grissom, Sara, Catherine et al.) television scripts from series 1:
- 1X01, Pilot, original air date on CBS Oct. 6, 2000. Written by Anthony E. Zuiker, directed by Danny Cannon.

- 1X02, Cool Change, original air date on CBS, Oct. 13, 2000. Written by Anthony E. Zuiker, directed by Michael Watkins.