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Arkhangel

  by James Brabazon


(about 437 pages)
109,372
total words
of all the books in our library
57.68%
vividness
of all the books in our library
7.29%
passive voice
of all the books in our library
2.64%
all adverbs
of all the books in our library
0.86%
ly-adverbs
of all the books in our library
1.78%
non-ly-adverbs
of all the books in our library

clippings from this book

We’ve analyzed hundreds of millions of words, from thousands of different authors, training our linguistic models to recognize the most vivid words in the English language… the words that create the most intense sensory experiences: colors, textures, sounds, flavors, and aromas.

Based on our analysis, we’ve scanned through the pages of this book to find the two pages at the extremes, both the most-passive and the most-vivid pages, so that you can compare them side-by-side and see the difference:

MOST PASSIVE PAGE
MOST VIVID PAGE
what you’re saying, he can’t have been a Russian. The dates don’t work, do they?’ He looked around for the waitress again. ‘I wonder if they have bagels? I mean, it’s Israel. They’ve got to have bagels, right?’ He was right. The shooter in the cottage couldn’t have been one of Avilov’s men. The dates didn’t tally. Until my name and face had popped up in The Times, Avilov hadn’t even known what to call me – at least, he hadn’t spoken my name in the ship’s hold. The same couldn’t be said of Doc. He could have been killed on Avilov’s orders – though my money was on one gunman, with that signature shot to the heart. Most terribly of all, if the shooter in the cottage had survived, and then killed Doc, I’d led him straight to my oldest friend’s door, after all. It was heartbreaking and infuriating in equal measure. As soon as one question was answered, another presented itself. But we were getting somewhere. While Doc had worked on my wounds, he’d told me that I’d been lucky to find him, that he’d had a shooting trip planned. And there’s good shooting in Donegal in January – snipe and woodcock, particularly. The more I looked at everything, the more it seemed Doc must have been the intended recipient – even if he might not have known he was, or what the banknote signified. But as soon as he’d spotted the name of my mother’s birthplace, he – like me – would have unconsciousness. Pain in my head: deep, throbbing, uncompromising pain that beat my skull from the inside, pushing brain against bone. My head felt full, as if it were filled with blood. As if it would burst. Pain in my back. A long, searing, tearing along my spine, flaring out across my ribs, gripping my stomach. My shins, calves, thighs burned. Pain so bright it had colour. Pain so hard I could see it. Light. Swinging, reeling in stark, brilliant white lightorbiting a blinding sun. Out of the light, colour. Infinity. Swirls of brilliant shapes merging, locking, shifting. The colours deepened with the thud-throb in my brain. Thud. Thud. Thud. I could hear. Sound. The anvil-song of metal striking metal, an undifferentiated, resonating peal that rang with the monstrous timbre of tolling sunken bells. But with echo, distance. And with distance, time. I was in the world. I was. Sweat crept up my torso, dripped into my nose, ran up my legs. My carotid artery bulged in my neck. The sound of blood roared in my ears. My tongue lolled on the roof of my mouth. I came to with a rush of realization and nausea and opened my eyes. My hands were tied behind my back. My legs were bound at the ankles. My ankles were fastened to a twist of rope. Back and forth, back and forth: my body swung upside down between two metal walls like a bleeding, lurching pendulum. With a start I crunched my abdomen

emotional story arc

Click anywhere on the chart to see the most significant emotional words — both positive & negative — from the corresponding section of the text…
This chart visualizes the the shifting emotional balance for the arc of this story, based on the emotional strength of the words in the prose, using techniques pioneered by the UVM Computational Story Lab. To create this story arc, we divided the complete manuscript text into 50 equal-sized chunks, each with 2187.44 words, and then we scored each section by counting the number of strongly-emotional words, both positive and negative. The bars in the chart move downward whenever there’s conflict and sadness, and they move upward when conflicts are resolved, or when the characters are happy and content. The size of each bar represents the positive or negative word-count of that section.

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