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One True Patriot

  by Sean Parnell


(about 376 pages)
94,092
total words
of all the books in our library
61.38%
vividness
of all the books in our library
6.47%
passive voice
of all the books in our library
2.57%
all adverbs
of all the books in our library
0.81%
ly-adverbs
of all the books in our library
1.76%
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
Or, was that really the reason? Hard to know without hearing it directly from Ted Lansky, which he hoped to do as soon as possible. So then, Steele had gotten himself a new keeper, that prick Goodhill, but that had no bearing on these events as far as he could tell. Then Pitts and Goodhill had sent him off to Paris to track down this alleged female assassin, and before he could say Joan of Arc, some Russian version of Odd Job nearly burst his heart right out of his chest in the same B&B where Stalker Six had spent his last night. But were the events even related? Did this Russian have anything to do with Raines’s death? And it was extremely rare that adversaries ever went directly after Alphas, because nobody knew who they were. Covers were airtight, trails weredustedelectronically and digitally. For anyone to target Steele with this Russian, they’d have to know who he was, where he was going, and where he was likely to camp for the night. Who’d know that except for… Someone in the Program. We’re not going there, Steele decided. There’s another explanation. We don’t have a traitor or a mole inside. It’s a disinformation operation, exactly what someone wants us to think. Somebody got me on facial recognition on some op somewhere, and that’s how they’re chasing me down. That’s how they got Stalker Six as well. Yeah, that’s it… But he wasn’t completely sure, and it was big, handsome man with thick, dark hair, blue eyes, and horn-rimmed glasses who looked like a Latino film star and cruised the blues venues. Even among the throngs of good-looking cowboys in Nashville, he’d be hard to miss. Lower Broadway was teeming with honky-tonks, bars, clubs, restaurants, and live music joints of all scales, the avenue’s sidewalks stained with spilled beers and vibrating with the echoes of boot heels and battling bands. Tin Roof was one of the most popular, and largest, with two floors of performance stages, wood plank dance floors, long chestnut bars, twirling disco balls, swinging pin spotlights, and effervescent inebriated line dancers. The prettiest rockabilly aficionados of both sexes packed into Tin Roof every night, and rarely went home lonely. On the third night, just after 1:00 a. m. Lila spotted Farro perched at the bar near the back of the main floor, on the left as you walked in from Broadway. She cruised by him once, then again to make sure, and slid up onto a stool around the bar’s back bend to make sure he could see her. He was dressed in a dark blue rough plaid shirt, black chest curls showing through the open collar, jeans, and Justin cowboy boots. The glasses gave him away. She was dressed in a black halter top, her long red tresses turned into waves by a curling iron, a very small green sequined skirt, and Tony Lama snakeskin boots. Her wrists jangled with Native American bracelets

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 1881.84 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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