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The Kremlin’s Vote

  by Andrew Turpin


(about 440 pages)
109,989
total words
of all the books in our library
35.44%
vividness
of all the books in our library
8.32%
passive voice
of all the books in our library
3.51%
all adverbs
of all the books in our library
1.38%
ly-adverbs
of all the books in our library
2.13%
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
after four o’clock. “Jayne, I’m sorry I’ve been a little elusive,” Simone said. “It’s been a difficult time, and I’ve not really felt like speaking to anyone, despite the floods of calls I’ve been getting. We had Curtis’s funeral on Friday.” “I’m glad you’ve called,” Jayne said. “That must have been traumatic, the funeral. I’m sorry I wasn’t there.” She felt somewhat snubbed that there had been no invitation from Simone, although getting there would have been impossible given she had been en route home from Helsinki. “We kept it small, a family funeral. I didn’t want any fuss or media attention.” “Of course, that was wise,” Jayne said. “How are you doing, Jayne? Can I help?” “You might be able to. We’re in a real bind here, trying to locate two other secretaries whom we believe were linked to Curtis, apart from the others who have been killed. I was hoping you could help.” She gave Simone their names. There was a slight pause. “Curtis knew them, yes. What do you want to know?” Jayne explained that she had discovered that Curtis had been the subject of a CID investigation in Afghanistan, to which Costello and the other secretaries of state had been linked. They believed that it was this that allowed them to be blackmailed into a larger scheme. “Do you know anything about that?” “The Afghanistan business? I thought that was forgotten,” Simone said. “He mentioned it a couple of times years ago but said it wasn’t grass, dodging between tree trunks. Jayne hoped that the darkness and the trees would provide enough cover to prevent them from being seen. As she ran, she heard the whine of an engine being thrashed in low gear and the squeal of tires on pavement as the car in the street accelerated. “FSB,” Shevchenko panted, unnecessarily. As they ran straight over the footpath that ran through the park and into the trees on the other side, Jayne glanced over her right shoulder and caught a glimpse of someone running along the footpath in their direction, maybe forty meters away. Bloody hell, who’s that? She felt certain the car hadn’t stopped yet. There came the screech of brakes behind them, confirming her thought, then the slam of a car door and a loud shout in Russian. “Stoy! Halt!” Jayne pulled an iron-gray wig from her side jacket pocket as she ran and pushed it down over her dyed blond locks, jammed a knitted wool hat over the wig, then grabbed a pair of brown plastic glasses from her breast pocket and put them on. Next to her, Shevchenko was also pulling on a wig, a short salt-and-pepper one, followed by a Russian fur hat with earpieces that she put on over the wig. Ahead of them, beyond the trees, was the street on the other side of the park. Jayne knew from her reconnaissance trip that there was a narrow alleyway that bisected the apartment buildings roughly halfway along. No car

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 2199.78 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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