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A Merciful Fate

  by Kendra Elliot

(about 378 pages)
94,502
total words
62nd PERCENTILE
of all the books in our library
95.15%
vividness
74th PERCENTILE
of all the books in our library
8.68%
passive voice
70th PERCENTILE
of all the books in our library
2.45%
all adverbs
18th PERCENTILE
of all the books in our library
0.98%
ly-adverbs
47th PERCENTILE
of all the books in our library
1.48%
non-ly-adverbs
7th PERCENTILE
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
Sandy fumed. Bree was her closest friend but hadn’t said a word. “She’ll be getting a phone call from me,” she stated. “Any broken car windows?” “No,” answered Truman. “Yesterday was the first incident, and it was just paint.” WHORE. Sandy stared at the huge letters. Why would Bree be targeted too? “Who does shit like this?” Samuel swore again. Fury radiated from him, and Sandy knew he wanted to hit someone. His anger didn’t make her nervous. She was pleased he’d responded with Truman. “Did you find some cameras?” Sandy asked Truman. It hurt to rely on someone’s kindness to help protect her property, but she simply didn’t have the money. She’d been in the red for months. If she had an accountant, he’d be in deep shock. Good thing I can’t afford one. “Uhhh… I should have some by tomorrow.” Sandy didn’t miss the glance Truman exchanged with Samuel. She narrowed her eyes at the two men, who she suspected weren’t being completely truthful. That makes three of us. “I would have installed one to cover this area.” Truman indicated the entire back side of her building. “It ticks me off that I’m too late. But we’ll definitely have them up by tomorrow evening.” “Absolutely,” Samuel chimed in. “We’ll have the asshole the next time he tries anything.” Why am I not reassured? She didn’t want to think about what the offender might do next time. During Truman’s last visit she’d been frustrated. Today that frustration had been swung open. Oh shit. “Mrs. Ingram?” he shouted. “Are you here? It’s Ollie.” He took one step into the house and listened hard. Silence. Is she asleep? Truman’s going to have my head. “Mrs. Ingram?” he yelled again. “Anyone home?” A small noise reached him. It sounded like a puppy. “Hello?” He took three more steps into the home, moving past the living room on his right and speeding toward the kitchen at the back of the house. “Mrs. Ingram?” he called in a normal voice. The puppy whined again. Ollie took a few fast steps and found himself in the kitchen. And nearly puked. Dear God in heaven. Oxygen vanished from the room and he sucked for air. Bree was tied to a wooden chair, her head slumped forward on her chest. Blood soaked her clothing and had puddled under the chair on the linoleum. One arm was clamped to the table. Her hand flat on its surface. A bloody mallet and a knife lay beside her hand. Along with two severed fingers. Ollie flung himself at the kitchen sink and heaved, barely making his target. Her fingers. He vomited again. Bree whined. A high-pitched, wet, choking sound. She’s alive. He spun toward her, wiped his mouth with a towel, and knelt next to her chair. He pushed her bloody hair out of her face and clenched his teeth at the sight of the abuse. Both her eyes had swollen shut. Her nose was bloody and split. Bleeding abrasions

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 1890.04 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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