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Virtual Vandals

  by Tom Clancy


(about 208 pages)
51,881
total words
of all the books in our library
45.79%
vividness
of all the books in our library
7.91%
passive voice
of all the books in our library
2.70%
all adverbs
of all the books in our library
0.97%
ly-adverbs
of all the books in our library
1.73%
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
computer was still faster than Matt would have been. An image formed on the holo-screen. It was a story about a memorial service for Marian Falk, Rob’s mother. She’d been crossing the street when she became the victim of a hit-and-run driver. Matt had often read about people’s blood running cold. But this was the first time he’d actually felt the sensation. Police had caught up with the driver, who’d turned out to be a Middle-European diplomat, driving drunk. The man hadn’t been brought up on charges, however, because he’d claimed diplomatic immunity. He’d even run back to his home country, escaping scot-free. That’s right, Matt remembered. Rob Falk’s father had been with the government, in the Customs Service. Ironically, his job had been to work with foreign diplomats about trade shipments entering and leaving the country. There were no more references to Rob Falk in the newspaper, and Matt knew why. Mr. Falk had not done well in his job after the accident. Things must not have been too pleasant at home, either. Rob’s classwork had begun to suffer. David Gray had known the guy—he’d said that Rob had begun to lose himself in his computer. In the end, Mr. Falk had lost his job and Rob had lost his Bradford scholarship. Matt turned off his computer. A kid who’d retreated into his computer, who had good reasons to hate diplomats. Now he’d come back out, recruited a bunch of diplo-brats to commit illegal acts… and maybe had image began to transform. Cat’s shining blond hair turned mousy brown, shrinking back into a severe haircut that, even though it was short, made her hair look stringy. Her heart-shaped face lengthened, the cheeks sinking in, her jaw growing long. Her lips flattened out into a tight line, and her eyes went from blue to a washed-out hazel. The sweater and jeans morphed into a baggy, unflattering jumper dress covering a cheap, plain white blouse. Bony wrists and nail-bitten hands stuck out from the too-short cuffs. Matchstick legs and ugly brown shoes emerged from the too-long skirt. Caitlin looked down at her altered self and let out a horrified scream. “My hair! My clothes… the rest of me! What did you do?” she demanded. “Don’t burst a valve,” Matt told her. “It’s just a proxy. You’ll need it to get in—just as I’ll need this.” He activated his proxy program, turning into a gangly redheaded boy with a freckled baby-face, wearing a not-quite-clean white shirt, a too-short tie, and dress pants that were a good inch and a half too short, showing off white gym socks. Caitlin looked at him and shuddered. “Tell me that’s not the way you actually look,” she begged. “You’d make a perfect Dexter.” She called up a virtual mirror and stood beside him, examining their reflections. “And you turned me into a real Nerdetta.” “So nobody would expect that’s you under there—or me.” Matt tapped the rumpled tie on his proxy self’s chest

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 1037.62 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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