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Gambit

  by David Hagberg


(about 367 pages)
91,863
total words
of all the books in our library
33.54%
vividness
of all the books in our library
9.05%
passive voice
of all the books in our library
2.70%
all adverbs
of all the books in our library
0.86%
ly-adverbs
of all the books in our library
1.84%
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
have come so far with your little game and are still intact.” “What are you talking about, you son of a bitch?” Hammond demanded. He was angry and shaken because he was beginning to realize where the Russian was going. “That Mr. McGarvey hasn’t figured out yet who’s gunning for him and come here to return the favor.” “It’s not possible.” “Ah, but Ms. Patterson may have given up the clue that could help Mr. Rencke to unravel your plot.” “I didn’t do anything of the sort,” Susan flared. “But you did, my dear hedonist, by opening your mouth on camera in Seattle.” “What the hell are you talking about?” she asked. “I’m a movie star; the interview was expected of me. Had I ducked out, it would have caused all sorts of fucking speculations.” “You’ve bugged this house,” Hammond said. “Da,” Tarasov said. “I’ll hire people to dispose of them.” “They won’t be found. Nor will the others we’ve placed here and there.” “I’ll get someone who’s good enough.” “But mine are the best. You can’t imagine the people we listen to and the stories I could tell.” “Your friends are Russian spies?” Susan demanded. Tarasov shrugged. “I have many friends, my dear lady, including you and Thomas.” “My jet is on its way back to LA for its annual maintenance inspection. Your bugs will be found.” Tarasov was unconcerned. “Not unless the mechanics are looking for them.” Hammond sat back, resigned. “You’re here. What do you want?” “We’ve Oxford or Harvard accent depending on what passports they were carrying. They had booked a suite overlooking the lake for their three-day stay and presented an American Express platinum card at check-in. He was dressed casually in a soft gray Armani suit, a white silk shirt open at the high collar, Gucci loafers, and a blond wig covering his dark hair, while Li wore a short off-white skirt, spike heels, and a sheer, nearly see-through soft yellow blouse, under which she wore a skin-tone bra. Her wig was short and red. Their appearances matched their passport photos. They meant to call attention to themselves. In Hammond’s parlance, they were just at the edges of the players circuit, a little too flashy, but nearly there. Heads turned when they walked into a lobby or bar. Upstairs, they tipped the bellman well and ordered a bottle of Krug from room service. When it came, they each had a couple of sips, and then Li poured the remainder of the bottle down the bathroom sink. Taio took a pair of matching shoulder bags from one of their suitcases, and they packed them with jeans, a light pullover sweater and boat shoes for him, a chambray shirt, spangly jeans, and pink Sketchers for her, plus two sets of American passports and driver’s licenses for each of them in the names Frank and Judy Kane from Waltham, Massachusetts, and George and Carolyn Schilling from Minneapolis, Minnesota, that they’d hidden in the lining of the suitcase

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 1837.26 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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other books by David Hagberg

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