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Agent in Place

  by Mark Greaney


(about 677 pages)
169,129
total words
of all the books in our library
39.28%
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 milled about, limo drivers stood by their freshly polished vehicles in nearby lots, and private security manned the streets and sidewalks. But the real action was inside. Through the monumental bronze doors cast by Christofle, up the grand marble staircase, and in the opulent Salle des Lustre, some three hundred well-dressed men and women sat around a long glowing runway that ran below and between rows of crystal chandeliers. The room was packed shoulder-to-shoulder, and thumping music and flashing lights gave an energetic, almost manic feel to the scene. The announcer proclaimed the arrival of the winter collection, the crowd leaned in, and, one at a time, lithe models began marching authoritatively out onto the catwalk wearing dramatic velvet capes, thigh-high boots, and embroidered chiffon dresses. The hum of the crowd was unmistakably approving. In the ninth row, to the right of the runway, sitting at the southern end of the room and holding a camera and an iPad, a man in a charcoal Armani suit sat next to an elderly woman with a small poodle nestled in her arms. The man’s eyeglasses were as refined as his silk tie and handkerchief, and he looked on at the procession traversing the catwalk just like everyone else, craning his head, nodding along with each new look, and tapping notes into his tablet. The man had avoided the majority of the cameras, and even the lights from the runway did not reach to him in his seat. He was just a face

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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