Statistical style analysis theory

The statistical style analysis of motion pictures is primarily a systematic version of mise-en-scene criticism - or, more accurately, mise-en-shot criticism. We have already seen that Eisenstein invented the term mise en shot to focus attention on the way shots are staged - that is, the way the parameters of the shot translate the actions and events into film. The advantage of statistical style analysis over mise-en-sctne/shot criticism is that it offers a more detached, systematic, and explicit mode of analysis. Statistical style analysis characterizes style in a numerical, systematic manner - that is, it analyses style by measuring and quantifying it. At its simplest, the process of measuring involves counting elements, or variables, that reflect a film's style, and then performing statistical tests on those variables.

More specifically, there are three standard aims of statistical style analysis: (1) to offer a quantitative analysis of style, usually for the purpose of recognizing patterns, a task now made feasible with the use of computer technology. In language texts, the quantitative analysis of style and pattern recognition is usually conducted in the numerical analysis of the following variables: word length, or syllables per word, sentence length, the distribution of parts of speech (the different percentage of nouns, pronouns, verbs, adjectives, and so on in a text), calculating the ratio of parts of speech (for example, the ratio of verbs to adjectives), or by analysing word order, syntax, rhythm, or metre; (2) for the purposes of authorship attribution, in cases of disputed authorship of anonymous or pseudonymous texts (see Foster 2001); and (3) for purposes of identifying the chronology of works, when the sequence of composition is unknown or disputed (e.g. Plato, Shakespeare's plays).

The first aim, the quantitative analysis of style, involves descriptive statistics, and the second and third (authorship attribution and chronology) involve both descriptive and inferential statistics. As its name implies, descriptive statistics simply describes a text as it is, by measuring and quantifying it in terms of its numerical characteristics. The result is a detailed, internal, molecular description of the formal variables of a text (or group of texts). Inferential statistics then employs this formal description to make predictions. That is, it uses this data as an index, primarily an index of an author's style, or to put the author's work into chronological order on the basis of measured changes in style of their work over time. Whereas descriptive statistics produces data with complete certainty, inferential statistics is based on assumptions made by the statistician on the basis of the descriptive data. These assumptions only have degrees of probability rather than certainty.

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