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Criss Cross

  by James Patterson


(about 313 pages)
78,257
total words
of all the books in our library
47.53%
vividness
of all the books in our library
7.16%
passive voice
of all the books in our library
2.33%
all adverbs
of all the books in our library
0.65%
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
obsessions get the better of you. I’m smelling lawsuit.” “So much for coming clean,” Mahoney said, looking disgusted. “I guess we’re done here.” “No,” Rivers said. “And there will be no lawsuit.” “Dwight—” his attorney began. “No lawsuit, Sheila,” he insisted. “Even if they hadn’t been behind me, I would have been going way too fast for the road conditions. If they hadn’t been chasing me, I might be dead.” “Well, that is absolutely not the way I see it.” Rivers fixed his eyes on me. “He’s your Professor Moriarty, isn’t he, Cross? This M?” I got the reference to Sherlock Holmes’s ultimate nemesis and shrugged. “You could say that,” I said. “Holmes became too obsessed with Moriarty. Because of that, he almost died.” “I remember.” Rivers watched me closely. “I don’t know whether to be flattered or disgusted by the fact that you thought I could be M— or, rather, your computers did.” “I apologize for the computers’ and my actions.” He laughed. “One thing I learned in the tech world is that you never apologize for a computer’s performance. It did what its programmer told it to do. Nothing more. Nothing less.” “Dwight,” his attorney said. “I think that—” His eyes brightened. “You’ve got him now, don’t you, Dr. Cross? M? He has to be on the security tapes. You’re close, aren’t you?” “If M was the deliveryman, we are. I hope so.” Cowles chewed her lip. “But how did M know you were watching me? How did sitting at a table. One was in his thirties, wearing a gray suit that didn’t fit him very well and a tie that looked like it might have been a clip-on. The other, who had his back to us, wore a sharply tailored blue sport jacket, khaki pants, and blue socks with white polka dots. His hair was jet-black and slicked back with some kind of pomade. This had to be Perry Singer. When we got around the table, we discovered a man in his late eighties sipping an espresso and nibbling at a chocolate cupcake he held with shaky hands. He wore a starched white shirt and a bow tie that matched his socks. A fancy cane rested against his thigh. He didn’t seem to notice us even when Sampson muttered, “This is supposed to be our suspect? I’ve taken an intense dislike to Bernard Mountebank.” “The British have an odd sense of humor,” I said. “Mr. Singer? Perry Singer?” The old man started. “Do I know you?” he asked in a soft Southern accent. We showed him our badges and IDs and told him we were working on a homicide investigation. “Just tying up some loose ends,” Sampson said. “Nothing to be alarmed about.” Mr. Singer shrugged. “Okay. How can I help?” After showing him the tie in the evidence bag, I said, “Do you own one of these ties? It’s a Kiton, the kind they sell at La Cravate.” He fumbled in his breast pocket, found glasses

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 1565.14 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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