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The Altman Code

  by Robert Ludlum


(about 560 pages)
140,069
total words
of all the books in our library
47.89%
vividness
of all the books in our library
7.72%
passive voice
of all the books in our library
2.96%
all adverbs
of all the books in our library
1.18%
ly-adverbs
of all the books in our library
1.77%
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
Shouldn’t it be over? Shouldn’t we have heard? Not even a word about my father?” “I don’t know, Mr. President. Colonel Smith knows the time frame.” Klein could sense the president’s nodding. “Yes, of course he does.” “He’ll do his best. No one’s best is better.” Again the affirmative nodding somewhere in the White House, as if the president were sure it would all work out, although a large part of him feared it would not. “I have to get the manifest, and then I have to get a copy to Niu Jianxing in Beijing. But now it’s too late, isn’t it? There’s no time to get even a copy to China and hope that’s enough to convince the hardliners. They’d laugh at a fax, or at a copy sent over the Internet. They could be too easily counterfeited. Or at least, if we’re right and there’s someone inside Zhongnanhai who wants war, there’s no way he’d have to believe anything short of the actual manifest.” “Jon will think of something,” Klein said reassuringly. But he had no idea what that could be. Neither did the president. “In an hour, maybe less, I’ll tell Brose to give the order. We’re going to have to board the Empress. I don’t see any way around it, dammit. You did your best. Everyone did their best. All we can do now is hope and pray the Chinese back off, but I don’t see that happening.” “No, sir. Neither do I.” The silence was useless here.” The microwaves sounded, announcing the food was ready. He brought the steaming platters and bowls and sat down again. “They want you ready to lead, if they ever get free. I assume you’re not the only one sent away to be educated.” “Of course not. There have been several dozen of us over the years, including my sister.” “Does the world know about you Uighers? What about the United Nations?” Asgar heaped stewed mutton cubes, onions, peppers, ginger slices, carrots, turnips, and tomatoes onto his plate, and Jon did, too. From the large bowl they took handfuls of a thick fried rice dish with more carrots and onions. As Asgar ate, he dipped the cubes of mutton into the dark liquid in the smaller bowl and accompanied it with one of the crisp pancakes, held like a slice of bread. Jon imitated him and found the food spicy and delicious. “The U. N.?” Asgar said between mouthfuls. “Of course, they know about us. But we have no standing, while China has an embarrassment of it. We want our land for growing crops and grazing our animals. China wants it because it’s rich. Oil. Gas. Minerals. You like the mutton?” “It’s delicious. What do you call the crisp flat fried bread?” “Nang.” “And the rice?” Asgar chuckled. He laughed a lot for someone who spoke so bitterly. “It’s calledeaten with the hands.’ He shrugged. “It’s always been the same for all the peoples of Central Asia. We rode

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 2801.38 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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