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A Single Source of Truth

  by Stewart McDonald

(about 437 pages)
total words
of all the books in our library
of all the books in our library
passive voice
of all the books in our library
all adverbs
of all the books in our library
of all the books in our library
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:

a grudge on, which must have disappointed his pursuers. ‘Anyway,’ said Farber, ‘it was a confidential interview.’ ‘Con-fi-den-tial?’ said Beckford, accentuating every syllable as if it was the most preposterous thing he’d ever heard. ‘They recorded the interview, right? Audio? Video? Now it’s data, which means it’s freely available to these people. Like stealing light from the sun.’ ‘I didn’t tell them we’d been in contact since your warrant was put out. If they were going to use me against you it would have already happened by now.’ Beckford took a few soft breaths before he realised she was probably right. These people operated well ahead of the game. Beckford kept falling into the trap where he thought he’d outsmarted them, but really that couldn’t be further from the truth. They didn’t need Farber as bait, they had every beat bobby in London looking for him now. ‘The computers from my apartment, where are they now?’ ‘I’m still trying to find that out.’ Beckford sighed, ‘I guess it doesn’t matter, they’re going to make sure there’s enough incriminating evidence on them to put me away for good.’ ‘You haven’t done anything wrong. Your name will be cleared, it’ll just take some time.’ ‘I wouldn’t live to see it cleared,’ said Beckford. ‘They want me inside so they can bump me off. That’s the only way they’ll cover this up.’ Beckford was so exhausted that the reality of the situation still hadn’t hit home properly. It was as if he was Farber was walking through was cold proof of that. Discarded beer bottles, cans and plastic cups lined the walls of the corridor like runway lights, each one frozen in the state it was left in barely a few hours earlier. A pungent aroma of stale booze and cannabis filled the air, bringing back memories of every hangover Farber had ever had. She passed a stoved-in pumpkin on her left, the red candle wax having spilled out across the carpet and solidified like a dried bloodstain. Somewhere behind her a collection of glass bottles clattered like bowling pins. ‘Bloody students,’ said Detective Sergeant Leonard Staedler. Farber stopped and watched as he crouched on one of his dodgy knees, letting a compressed breath hiss through his lips as he righted the bottles he’d knocked over. A pair of curious students passed, one wearing a skeleton costume with black and white makeup smeared over his faceundoubtedly a work of art before he’d spent the night lip-locked with the bloodied nurse who walked alongside him. Halloween costumes are getting more impressive each year, thought Farber. The Detectives continued and turned a corner, making their way towards a room buzzing with police activity. A girl with black hair and a yellow blouse scurried by, tear-streaked mascara running down her pale cheeks. A few doors away they came to the backs of a group of gathering adolescents. ‘Out of the way please,’ said Farber, her stern, authoritative tone making their heads spin like startled owls

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 2186.44 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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