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First Kill

  by David Hagberg


(about 374 pages)
93,406
total words
of all the books in our library
34.64%
vividness
of all the books in our library
9.01%
passive voice
of all the books in our library
2.64%
all adverbs
of all the books in our library
0.87%
ly-adverbs
of all the books in our library
1.76%
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
is, forgot to sign. And no one upstairs wants to deal with it. Frankly I think someone screwed up and doesn’t want to admit it.” “Might be better to let sleeping dogs lie.” “I intend to do just that, which is why I called you personally. All I want is an operational name to tidy the record.” “I’ll have Mrs. Goldberg pull the files for you.” Plonski signed out, telling the chief clerk that he was going home for some sleep and wouldn’t be back till tomorrow, and was on the road a few minutes before nine. He stopped at a Shell station, where he filled up his green Chevy Impala and phoned Pat. “I’m home sleeping. If anyone calls, tell them I’m not to be bothered until dinnertime.” She was angry. “Are you with Mac?” “Honest to God, no.” “But you’re doing something for him that no one at work is supposed to know about. That’s it, isn’t it?” “I’ll explain when I get home.” “Goddamnit, Janos, I’m afraid.” “Don’t be,” he said. Mac hadn’t warned him specifically to be careful who he told, but the implication had been there. And Trotter had been lying through his teeth this morning. The problem was that already too many people apparently knew what Mac had been ordered to do. It was sloppy; more than that, it was incredibly dangerous. But the thought had struck him even before Trotter had left his office that whoever the East Coast American was who’d been have at San Antonio. The explosion was apparently to be used as a diversion. He was either coming by sea or leaving that way.” “Or both,” Baranov said. “Si.” Or neither, Baranov said to himself after he hung up. He put his tea aside, took off his pool jacket and swim trunks, got an empty glass and sat down beside the Vargas, his feet in the pleasantly warm water. He held out his glass and Karina poured some brandy for him. “Pretty morning,” she said. “Indeed it is,” Baranov said. He took a drink. Harsh, filthy stuff compared to vodka. Even champagne—a good vintagewas better. But while in Rome. “Good news, you two.” Matias glanced at the phone. “Who was it?” “Torres. He said that your would-be assassin is dead.” The general nodded, but Karina raised her glass in salute. “That’s good, Vasha. Very good. We need to celebrate.” “My bedroom?” Baranov asked. The general nodded again, a faint smile on his thin lips. “Too bad we don’t have any films.” “Yes, too bad,” Baranov said, rising. “Bring the bottle.” It was nearly noon before the Vargas left, neither of them bothering to take a shower, which bothered Baranov to no end. He’d never liked dirty people. After he’d cleaned up and got dressed in light linen slacks and a loose cotton shirt, he went out to the pool, where the cook laid out a lobster salad, croissant, butter and a bottle of Chopin, his favorite Polish vodka

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 1868.12 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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