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The Firm

  by John Grisham


(about 542 pages)
135,449
total words
of all the books in our library
77.28%
vividness
of all the books in our library
7.52%
passive voice
of all the books in our library
2.84%
all adverbs
of all the books in our library
1.02%
ly-adverbs
of all the books in our library
1.83%
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
stationed there. Spanish had taken four years, but he was forced to learn it from a dictionary in the prison library. French was his latest project. “I’m fluent, I guess,” Ray answered. “It’s kinda hard to tell in here. I don’t get much practice. Evidently they don’t teach French in the projects, so most of these brothers here are unilingual. It’s undoubtedly the most beautiful language.” “Is it easy?” “Not as easy as German. Of course, it was easier to learn German since I was living there and everybody spoke it. Did you know that fifty percent of our language comes from German through Old English?” “No, I didn’t know that.” “It’s true. English and German are first cousins.” “What’s next?” “Probably Italian. It’s a Romance language like French and Spanish and Portuguese. Maybe Russian. Maybe Greek. I’ve been reading about the Greek isles. I plan to go there soon.” Mitch smiled. He was at least seven years away from parole. “You think I’m kidding, don’t you?” Ray asked. “I’m checking out of here, Mitchell, and it won’t be long.” “What are your plans?” “I can’t talk. But I’m working on it.” “Don’t do it, Ray.” “I’ll need some help on the outside, and enough money to get me out of the country. A thousand should do it. You can handle that, can’t you? You won’t be implicated.” “Aren’t they listening to us?” “Sometimes.” “Let’s talk about something else.” “Sure. How’s Abby?” “She’s fine.” “Where is she?” “Right now she’s veal was tender; then removed. She poured the oil from the pan and added wine and lemon juice until it was boiling. She scraped and stirred the pan to thicken the sauce. She returned the veal to the pan, and added mushrooms and artichokes and butter. She covered the pan and let it simmer. She fried bacon, sliced tomatoes, cooked linguine and poured another glass of wine. By seven, dinner was ready; bacon and tomato salad with tubettini, veal piccata, and garlic bread in the oven. He had not called. She took her wine to the patio and looked around the backyard. Hearsay ran from under the shrubs. Together they walked the length of the yard, surveying the Bermuda and stopping under the two large oaks. The remains of a long-abandoned tree house were scattered among the middle branches of the largest oak. Initials were carved on its trunk. A piece of rope hung from the other. She found a rubber ball, threw it and watched as the dog chased it. She listened for the phone through the kitchen window. It did not ring. Hearsay froze, then growled at something next door. Mr. Rice emerged from a row of perfectly trimmed box hedges around his patio. Sweat dripped from his nose and his cotton undershirt was soaked. He removed his green gloves, and noticed Abby across the chain-link fence, under her tree. He smiled. He looked at her brown legs and smiled. He wiped his forehead with a sweaty forearm

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 2708.98 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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