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Agent in Place

  by Mark Greaney


(about 677 pages)
169,129
total words
of all the books in our library
38.55%
vividness
of all the books in our library
7.14%
passive voice
of all the books in our library
2.61%
all adverbs
of all the books in our library
0.78%
ly-adverbs
of all the books in our library
1.83%
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
might give up information under torture. I can’t let Ahmed know I’m helping the people who’ve kidnapped me. If he knew that, he would definitely kill my son.” Court realized this would make his job more difficult, but he also realized this was the right move for Bianca to make. It made Jamal a little bit safer, and it put Court at more risk. If he had been the boy’s parent, he would have done exactly the same thing. “I understand.” Court stood, but Bianca said, “How do you plan on traveling with a four-month-old?” Court cocked his head. He didn’t really understand the question. “I’ll just carry him, I guess. How much can he possibly weigh?” Bianca closed her eyes. Suddenly Court could see disappointment on her face. “You haven’t even thought about this, have you?” “Full disclosure… I’ve never snatched a baby before. This will be a first.” “Do you have children?” When she didn’t get an answer, she said, “No… you wouldn’t, would you?” She sighed. “Well, I can tell you one thing. You can’t do this alone. He needs food, care. You don’t look like someone who can take care of a baby.” Court just stared back at her. “His au pair is there. She is with him all the time, and she can take care of him until you bring him to me. Her name is Yasmin. She will help you.” “Why would she help me?” Bianca said, “She will have no choice. Azzam would caustic solvent on the fingertip to roughen it up, and the patient grunted with pain, but he urged the surgeon to continue. A silicone gum was spread in a thin sheet on the skin to protect it, and then Qureshi took a soggy wet piece of live natural sponge out of a dish of salt water with a pair of forceps. This the surgeon cut to the size of Drexler’s fingertip, taking his time to make a precise little oval. Some high-end fingerprint readers have a feature designed to ensure that the prints are not silicone imprints or harvested from cadavers by using software to compare the spatial moisture pattern of a finger’s pores to detect natural secretions. But Drexler knew a spoof for this. The small organic sponge, saturated with salt water and a little glycerin and placed carefully under the cadaver print, kept the dead skin moist longer, and it allowed just enough dampness to register on the surface. Once the sponge was glued in place with a latex adhesive that bonded with the skin, the surgeon lowered surgical eye loupes over his eyes to magnify Drexler’s fingers. He very carefully reached a set of straight-blade forceps into a dish marked “L-Hand, 5” in Arabic to indicate the pinky finger, and he retrieved Veeti Takala’s pink flesh. Drexler was surprised how thick the dead skin was; he had pictured something translucent, like an onion peel, but the surgeon held up a dense and opaque chunk of human tissue

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 3382.58 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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