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The Sigma Protocol

  by Robert Ludlum


(about 771 pages)
192,836
total words
of all the books in our library
45.84%
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 slowly, his helmet lamp illuminating the breathtaking formations. Some of the stalactites were fragile soda straws, slender and delicate, tapering to points as sharp as knitting needles; too, there were the banded calcite stumps of stalagmites, the occasional column formed by the meeting of a stalactite and a stalagmite. Water oozed down the walls and seeped down the stalactites, the steady drip-drip-dripping into water on the cave floor the only noise in the eerie silence. Hardened flowstone formed terraces, and translucent sheets of calcite hung down from the ceiling like drapery, their edges serrated and sharp. Everywhere was the acrid ammonia stench of bat guano. “Ah, look!” Neumann said, and Ben turned to see the perfectly preserved skeleton of a bear. There arose a sudden papery thunder of hundreds of batwings; a cluster of hibernating bats had been awakened by their approach. Now Ben began to feel the chill. Somehow, for all his precautions, water had seeped into his boots, dampening his socks. “Come,” Neumann said, “this way.” He led them into a narrow passage, one of several corridors off the gallery barely distinguishable from the others. The ground gradually rose up before them, the walls growing closer together, almost to a bottleneck. The ceiling was barely head-high; had Ben been any taller than his six feet, he would have had to stoop. The walls here were icy, the seep water at their feet frigid. Ben’s toes had begun to go numb. But lithe Neumann scrambled up the steep crevice

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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