A Comparison of Methods for the Attribution of Authorship of Popular Fiction

Introduction

In this poster we present the stylistic analysis of a number of popular fiction genres. Popular fiction generally receives less academic attention than literature, but its ability to draw the reader into the story is noteworthy. In previous work (Opas and Tweedie, 1999a, 1999b) we have examined measures of stance in an attempt to quantify this degree of reader involvement. In this paper we turn to measures used to discriminate between authors, in order to find consistent differences between genres and authors.

Textual Sources

We have taken texts from three distinct sources: romance novels, detective novels and American short stories. Our total corpus is 590,000 words. We have analysed romance novels published between 1990-1996 from the Harlequin Presents and Regency Romance series. We have also analysed Danielle Steel's works, which are classified as women's fiction or 'cross-overs'. The romance texts make up 245,000 words. The detective fiction part of our corpus is made up of popular contemporary female authors published in the 1990s, i.e. Cornwell, Grafton, James, Leon, Peters, and Rendell. Where an author has created many detectives, we chose the most well-known one to represent that author. Some of the detectives are male and others female and we expect them to express stance differently. These texts make up 295,000 words. Short stories were also taken from the works of Carver and Barth. These make up almost 50,000 words.

Methods

We will compare and contrast the results from three analyses of these texts. The analyses are based on methods used in determining authorship: the frequency of the most common words, letter frequency and measures of vocabulary richness. The data from each of these procedures is then used in a principal components analysis in order to identify the most important elements.

1) Word frequencies The use of principal components analysis of the most common words to determine authorship was proposed by Burrows in 1988 and has become an essential tool for stylistic analysis. Here, the most commonly-occurring forty words were employed. Their frequencies were measured and standardised for text length. A principal components analysis was then carried out and the texts plotted in the principal components space. The first two principal components corresponded to 32.2% of the total variation. The first principal component separates the romantic Steel texts, with high negative scores, from the American short stories which have high positive scores. Detective stories by Sue Grafton and Patricia Cornwell also have high positive scores on this axis. The second principal component appears to act as a rough genre separator; romantic texts tend to have positive scores and all of the detective novels have negative scores. Consideration of a loadings plot indicates that the Steel texts use a high proportion of "she", "her" and "they", while the short stories use "at", "said" and "on". The Grafton and Cornwell texts are written in the first person and this is highlighted by their use of "me", "my" and "I".

2) Letter frequencies Ledger and Merriam use letter frequencies in their analysis of Shakespearean texts with remarkable success. Here we consider the relative frequencies of 'A' - 'Z', with capital and lower-case letters amalgamated. These 26 variables are then subjected to principal components analysis. The results are plotted in the first two dimensions of the principal components space which account for 34.5% of the total variation. In this analysis the separation is not as good as the word frequency analysis. The American texts tend to have high negative scores on the first principal component, while the texts by P. D. James have very high positive scores.

3) Measures of Vocabulary Richness A great number of measures of vocabulary richness have been proposed. Tweedie and Baayen (1998) carry out a review of these measures and find that two, K and Z, contain the vast majority of the information from the author's vocabulary. Yule's K measures the 'repeat-rate' used by the author, while Orlov's Z measures vocabulary richness in the sense of the number of different words used. We therefore plot the texts in the K-Z plane. As might be expected, the American short stories are found to have a low repeat rate and high vocabulary richness. The Steel texts have a higher richness than the other romantic texts, but the detective and romantic fiction texts are not separated by this analysis.

3. Conclusions

These three analyses offer views of different facets of the style of popular romantic and detective fiction. The genres are most clearly separated when the most common words are used as data, while the letter frequency analysis is, not surprisingly, more affected by the particular names of heroes or heroines. The measures of vocabulary richness distinguish clearly between the more popular texts and the short stories. At the conference we shall also present the analysis of markers of stance, used in Opas and Tweedie (1999a, 1999b).

References

Burrows, J. F. (1987) Word patterns and stay shapes: the statistical analysis of narrative style. Literary and Linguistic Computing 2(2): 61-70.
Ledger, G. and Merriam, T. (1994) Shakespeare, Fletcher and the Two Noble Kinsmen. Literary and Linguistic Computing 9(3): 235-248.
Opas, L. L. and Tweedie, F. J. (1999a) The Magic Carpet Ride: Reader Involvement in Romantic Fiction. Literary and Linguistic Computing 14(1):89-101.
Opas, L. L. and Tweedie, F. J. (1999b) Come into my World: Styles of Stance in Detective and Romantic Fiction. Abstracts of the ALLC/ACH conference 1999, Virginia, 247.
Tweedie, F. J. and Baayen, R. H. (1998) How Variable May a Constant Be? Measures of Lexical Richness in Perspective. Computers and the Humanities 32(5): 323-352.