Narrative Statistics: Figuring Out a Distribution of Words in Sentences

This entry is part 1 of 3 in the series Narrative Statistics

Thursdays are my research days. I have a couple things cooking away that I’m not quite ready to write about yet, but I want to take a little time today to explore something that I plan on doing a lot more once my cooking is done.

I’m interested in studying narrative as a dynamic system. That is, there are several variables at play that determine the direction of a narrative. There are plot dynamics, character dynamics, and thematics that an author plays with to construct the story. They all interact in complex ways. A particular plot might require certain type of characters. A particular character might not fit certain types of plots. Some plots and characters don’t illustrate well certain themes. The author has to select the right plots, characters, and themes (and write well) for the reader to enjoy the story. 

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Narrative Statistics: Revisiting Sentence Length Statistics and What to Do Next

This entry is part 2 of 3 in the series Narrative Statistics

Last week, we explored the Poisson distribution as a possible distribution of sentence lengths. If you look at the figure for Hunter Crackdown, the Poisson seems reasonable, but it breaks down when looking at other works. In this post, I’d like to go back and try to derive a distribution that has the same qualitative features as the distributions we saw for each of the works. Then, I want to discuss a bit what we might want to do next.

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The Role of Statistics

This entry is part 3 of 3 in the series Narrative Statistics

English: Hydrogen Density Plots for n up to 4.
Image via Wikipedia

In the Narrative Statistics series of posts, I’m exploring different ways to characterize fiction using statistics. I’m recovering from a flu or cold as well as a nasty cough that followed, so instead of delving into deep math, I want to review what I see as the role of statistics, at least for this series. Many people consider statistics to be magical formulae that give questionable answers. In the humanities, there seems to be a lot of mistrust for statistics because people don’t understand them. 

I’ve been in the audience when someone has presented some statistical results and someone else comments that because the outliers obviously don’t agree with what they already believe to be true, the outliers must be mistakes and thus the statistical method must be suspect. They then turn around and ask what statistics can provide other than reinforcing what they already know. They first throw out any new information and then ask what new information the methods can provide. The profound lack of logic mystifies me.

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