Text Mining: The Shining

I completely skipped The Shining somehow, so we’ll circle back and do that one now.

The Shining (1977)

Stephen King’s third novel finds him cycling through doing his own take on all the classic horror bits: the avenging revenant of Carrie, updating Bram Stoker’s Dracula to the modern (in 1976) age in Salem’s Lot, and now the Haunted House – in this case, a whole haunted hotel. There’s an element of Shirley Jackson’s The Haunting Of Hill House in Salem’s Lot as well; the house that the villain Barlow moves into in the Lot is a long-time haunted house inhabited by cursed individuals. The Overlook Hotel has been the destination of rich, shady people since it’s inception and by the time full-time alcoholic/on-his-last-chance writer Jack Torrence comes around to be it’s winter caretaker, it’s charged with their energies: the awful, unspeakable emotions that were left behind and whose ghosts now bestow a strong, malevolent force of will upon the hotel.

Text Mining: The Long Walk

Now that we’ve established that there is a link between key scenes in the plot progress of a Stephen King novel and mapped sentiment peaks coded from the text, we can spend significantly less time on analyzing each peak to show this. This will allow us to go through books with a little less ponderous text.

The Long Walk (1979)

The Long Walk is another short Bachman novel about sexually frustrated young men. This time it’s about the contestants of a gruelling, cruel national sport instituted after America’s loss in the Second World War and the institution of military rule by “The Squads.” The backdrop is briefly described but evocative for that when it is mentioned. At any rate, the protagonist is one of 100 contestants who start the Long Walk. They have to keep walking at a certain speed or they are shot by soldiers who are driving around beside them. They get three warnings to get their speed back up, otherwise the guns ring out and down goes another contestant. It’s a pretty horrifying idea when it comes right down to it, if only for how weirdly plausible it is given the modern love of both spectacle and fascism. It’s also pretty psychologically taxing, especially once the weakest contestants die off and it becomes a game to walk your opponents into the ground.

Text Mining: The Stand

The Stand (1978)

So…it may behoove you to know that The Stand, King’s gigantic, bloated, sprawling epic, was picked by American adults in 2008 as their fifth-favourite book of all time. The Bible was #1 – this is America that was being polled, after all – but The Stand kept company with other books you may be familiar with: Gone With The Wind, The Lord Of The Rings, and the Harry Potter series. Generational touchstones, in other words. As a further fact, Generation X picked it as their #1 favourite (again, behind the Bible). That’s some big company, so an examination of this one should yield some interesting results.

Text Mining: Rage

Rage (1977)

Today we turn our attention to the first Richard Bachman book, Rage, a book that lives up to it’s name in as pure a fashion as you could imagine. If you haven’t found a copy of this yet, you might want to get on that: they aren’t making any more of them, at the behest of the author. As the events depicted in the book came into depressing vogue in the 21st Century, King feared that the portrayal of Charlie Decker would give aid and comfort to others in similarly desperate emotional situations.

It’s about a school shooter, you see.

Text Mining: Intro + Carrie

As mentioned in my previous post I’m examining Stephen King texts through the magic of text mining, using a number of tools in the R language, but especially through Julia Silge’s tidytext package. The book Text Mining With R: A Tidy Approach by Julia Silge and David Robinson was a godsend in explaining the process of using tidy data formats to store and analyze text-as-data. I will roughly summarize the basics to give you an idea as to what’s involved but there is a great deal more that can be done than I am covering here.

Literary Fun With Text Mining

My wife is doing her PhD in political science on the topic of political interest groups and how they use social media to disseminate information and reach new audiences, and how they utilize this new(ish wow we’re old) medium to effect voting behaviour. Part of this has meant learning how to mine Twitter data and analyze it through the R programming language; in order to provide technical support and to have someone to troubleshoot coding issues, I’ve also been learning to use R to mine and analyze texts. What I’ve been concentrating on, in order to learn the language and the processes, is using it to mine and visualize data gathered from fictional texts, specifically the bibliography of Stephen King. What I want to do is to analyze plot trajectories drawn from sentiment data – quantitative measures of emotional sentiment words based on established dictionaries used for that sort of thing. Research questions on this would include things like: is there a pattern that King has for his plots, based on emotional language cues? Is this pattern, if any, different from other well-known horror writers? Furthermore, are there established “archetypal” emotional plot patterns for horror books, and do these patterns differ when you switch genres – say, to fantasy, military science fiction, paranormal romance, etc. etc. down the fracture lines of human experience.

Interstitial Burn-Boy Blues

Stuart watched the kid shake and mutter to himself in the seat across the aisle. His skin looked waxy in the dingy interior bus lights, and Stuart was sure that if he reached across and caressed the kid’s forehead with the back of his hand that skin would be near to scalding. He ran his tongue along the back of his teeth and watched the kid carefully. No one else in the general vicinity seemed to be concerned. Stuart noticed an old man dozing in the seat behind the kid, and a young couple murmuring to each other beneath a blanket in the seat ahead of him.

50 Days Of Soundcloud #14

“Beggar”

I may have skipped a day. Eh.

This one is a filler track from Temporarily Abandoned Profiles, but one that I remember fondly. Brash, aggressive, noisy, almost punk rock. Good times.

50 Days Of Soundcloud #13

“The Long, Bloody Road To Hell”

This was back during a time when I was dealing with frenetic hand-drumming married to near-chaotic thumb piano lines. Early 2004, I think. A collection of increasingly ominous historical quotes from a variety of figures that ends with Rodney King’s sobbing plea to stop making it horrible for the old folks, and the kids.

Don’t forget to stop by the books page here to check out some fiction which you can use to subsidize my existence.

50 Days Of Soundcloud #12

“Formula Modernia”

BUY SELL BUY SLEEP

Feel free to check out some books: today’s featured titles include Disappearance, only 99 cents, which if you enjoy the action bits in books and you like apocalypse fiction you’ll enjoy; What You See Is What You Get, which manages to combine the specter of ag-gag laws with criminal trials that look more like reality TV than anything else; and 9th Street Blues, about a kid delivering cobbled-together drugs in the near future ruins of Woodward, OK (and is also the jumping-off point for my new serial novel, coming soon from ATM Publishing).