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Secrets of Harry Bright

  by Joseph Wambaugh


(about 392 pages)
98,105
total words
of all the books in our library
82.08%
vividness
of all the books in our library
7.17%
passive voice
of all the books in our library
2.46%
all adverbs
of all the books in our library
0.57%
ly-adverbs
of all the books in our library
1.88%
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
wanna talk to that service manager.” “He, uh, he’s… I don’t think he’s available. He may be off today. I’ll have to check and call you back.” “Listen,” Otto said, “this is a very serious investigation. There’s been lots and lots a man-hours expended and lots and lots a blind-alley chases. I wanna know something, and be absolutely sure when you answer me. Could you be… mistaken? That is, could your service manage r b e mistaken?” “Uh, how do you mean that?” “What if it was some other Rolls that came in that day? What if some other young guy was driving? Is it possible he’s confused? It would be a serious matter if a p olice investigation was geared around a… mistake . Someone could even get in trouble.” There were several seconds of silence and then the car dealer said, “Well, anything’s possible.” I know anything’s possible. Is it maybe more than possible that your service manager is mistaken?” It’s… at least very possible,” the car dealer said shakily. “I wouldI’d have to talk with him.” “Thanks very much,” Otto said. “If we have any more questions, we’ll call you.” “Do you think you’ll have more questions?” The car dealer sounded ill. “I doubt it,” the detective said. When Sidney Blackpool came back to the suite, Otto was all gussied up in his best golf outfit, the one with the pink argyle sweater. He was in the sitting room reading the newspaper. “Thought you might still be grunting like grizzlies, staggered back into the living room where Shamu braced against the wall and got Billy Hightower in a very good choke hold. “Jist… jist… like… like the cops do it!” he grinned, as he applied the forearm and bicep to Billy Hightower’s throat, pinching the carotid artery. Sidney Blackpool was making a move to use a kitchen chair on Shamu’s skull when Billy Hightower took three short strangling breaths, puffed his cheeks, dropped his chin and clamped down on Shamu’s hairy forearm with those huge broken teeth. It took perhaps three seconds, but then Shamu began howling. He leaped away from Billy Hightower as if the Cobra leader was on fire. Billy Hightower, with Shamu’s blood dripping down his chin, fell back against the wall wheezing and holding his throat. “MY ARM. LOOK AT MY FUCKIN ARM!” the bearded biker roared. There was a flap of skin and muscle hanging loose, and Otto Stringer thought he could see a tendon wriggling like a nightcrawler. Shamu was still staring in shock and pain at his ravaged arm when Billy Hightower drove his fist straight in like a saber thrust. He hit Shamu in the solar plexus and the giant crashed back against the wall blowing like an elephant. Then Billy Hightower did it again. The same shot in the same spot and Shamu’s head shuddered and his teeth cracked shut like a trap and he genuflected. Then Billy Hightower stepped back and affected a grin with black blood-flecked

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 1962.10 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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