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The Hunt for Red October

  by Tom Clancy


(about 654 pages)
163,424
total words
of all the books in our library
38.47%
vividness
of all the books in our library
8.46%
passive voice
of all the books in our library
2.73%
all adverbs
of all the books in our library
1.05%
ly-adverbs
of all the books in our library
1.68%
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
more. It would be the intelligence coup of all time.” “That’s true. But maybe they’re a little too eager.” “I don’t understand what you mean, sir,” Ryan said, though he understood it just fine. Pelt was the president’s favorite. He was not the Pentagon’s favorite. “They might take a chance that we might not want them to take.” “Dr. Pelt, if you’re saying that a uniformed officer would—” “He’s not saying that. At least not exactly. What he’s saying is that it might be useful for me to have somebody out there who can give me an independent, civilian point of view.” “Sir, you don’t know me.” “I’ve read a lot of your reports.” The chief executive was smiling. It was said he could turn dazzling charm on and off like a spotlight. Ryan was being blinded, knew it, and couldn’t do a thing about it. “I like your work. You have a good feel for things, for facts. Good judgment. Now, one reason I got to where I am is good judgment, too, and I think you can handle what I have in mind. The question is, will you do it, or won’t you?” “Do what, exactly, sir?” “After you get out there, you stay put for a few days, and report directly to me. Not through channels, directly to me. You’ll get the cooperation you need. I’ll see to that.” Ryan didn’t say anything. He’d just become a spy, a field officer, by presidential fiat. Worse, he’d be reported. Wood was in the sonar room in seconds, putting on earphones plugged into a tape recorder which had a two-minute offset. Commander Wood heard a whooshing sound. The engine noises stopped. A few seconds later there was an explosion of compressed air, and a staccato of hull popping noises as a submarine changed depth rapidly. “What’s going on?” Wood asked quickly. The E. S. Politovskiy In the Politovskiy’s reactor, the runaway fission reaction had virtually annihilated both the incoming seawater and the uranium fuel rods. Their debris settled on the after wall of the reactor vessel. In a minute there was a meter-wide puddle of radioactive slag, enough to form its own critical mass. The reaction continued unabated, this time directly attacking the tough stainless steel of the vessel. Nothing man made could long withstand five thousand degrees of direct heat. In ten seconds the vessel wall failed. The uranium mass dropped free, against the aft bulkhead. Petchukocov knew he was dead. He saw the paint on the forward bulkhead turn black, and his last impression was of a dark mass surrounded with the blue glow. The engineer’s body vaporized an instant later, and the mass of slag dropped to the next bulkhead aft. Forward, the submarine’s nearly vertical angle in the water eased. The high-pressure air in the ballast tanks spilled out of the bottom floods and the tanks filled with water, dropping the angle of the boat and submerging her. In the forward part of the submarine

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 3268.48 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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