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The Sigma Protocol

  by Robert Ludlum


(about 771 pages)
192,836
total words
of all the books in our library
44.68%
vividness
of all the books in our library
8.13%
passive voice
of all the books in our library
3.40%
all adverbs
of all the books in our library
1.47%
ly-adverbs
of all the books in our library
1.93%
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
us that whoever’s ordering the murders stands to gain financially from them. Has to be. Someone like Strasser, or even your father.” She looked at him. She couldn’t automatically rule it out. Even if he didn’t want to hear it. His father might have been a murderer himself might have blood on his hands, might have been behind the murders at least. But how to explain the intricate deception of Ostrow, the false CIA man? Might he have been somehow connected to the heirs to some vast hidden fortune? “Theoretically, I suppose, my father could be one of the bad guys.” Ben said. “But I really don’t believe it.” “Why not?” She didn’t know how far to push him on this. “Because my father already has more money than he knows what to do with. Because he may be a ruthless businessman, and he may be a liar, but after talking with Sonnenfeld, I’m coming to think that he wasn’t fundamentally an evil man.” She doubted Hartman was holding anything back, but surely he was hampered by filial loyalty. Ben seemed to be a loyal person an admirable quality, but sometimes loyalty could blind you to the truth. “What I don’t get is this: these guys are old and failing,” Hartman continued. “So why bother hiring someone to eliminate them? It’s hardly worth the risk.” “Unless you’re afraid one of them will talk, reveal the financial arrangement, whatever it is.” “But if they haven’t talked for half a century, what’s the shelves were rows of dusty glass bottles, some as small as the Mason canning jars Mrs. Walsh used to preserve fruit in, some two feet tall. Each bottle held a fluid of some kind, which Ben assumed to be a preservative such as formalin, slightly cloudy with age and impurities. And floating in them, like pickles in brine, one to a bottle … No, this could not be. He felt his skin erupt in gooseflesh. In each bottle was a human baby. The bottles were arrayed with ghastly precision. In the smallest were tiny embryos, at the earliest stage of gestation, little pale pink prawns, translucent insects with grotesque large heads and tails. Then fetuses not much longer than an inch: hunched, stubby arms and oversized heads, suspended in the shrouds of their amniotic sacs. Fetuses not much bigger but looking more human, bent legs and waving arms, eyes like black currants, floating in perfectly round sacs surrounded by the ragged halo of the chorionic sac. Miniature infants, eyes closed, sucking thumbs, a tangle of tiny perfectly formed limbs. As the bottles increased in size so did their contents, until in the largest bottles floated full-term babies, ready to be born, eyes closed, arms and legs splayed, little hands waving or clenched, severed umbilical cords floating loose, swathed in translucent wisps of amniotic sac. There must have been a hundred embryos and fetuses and babies. Each bottle was labeled in German, in neat calligraphy, with a date (the date ripped

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 3856.72 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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