(about 831 pages)
207,836
total words
of all the books in our library
|
64.01%
vividness
of all the books in our library
|
7.41%
passive voice
of all the books in our library
|
2.87%
all adverbs
of all the books in our library
|
1.16%
ly-adverbs
of all the books in our library
|
1.71%
non-ly-adverbs
of all the books in our library
|
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 |
sorry he was, but felt there was nothing he could do to help. “Yes, there is,” insisted Marvin. “For a start, you could take out a policy yourself. That might just save my skin.” “I don’t think that would be wise,” said Pat, wondering what David would have advised. “Surely David wouldn’t have wanted to see me fired,” Marvin pleaded. “Have mercy on me, my friend. I just can’t afford another divorce.” “How much would it cost me?” asked Pat, desperate to find some way of getting Marvin off the line. “You’re going to get a million dollars in cash,” Marvin almost shouted, “and you’re asking me what it’s going to cost? What’s a thousand dollars a month to someone as rich as you?” “But I can’t be sure that I am going to get the million,” Pat protested. “That’s all been settled,” Marvin told him, his voice falling by several decibels. “I’m not supposed to let you know this, but you’ll be receiving the check on the thirtieth of the month. The company knows that your lawyer’s got them by the balls—you wouldn’t even have to make the first payment until after you’d received the million.” “All right,” said Pat, desperate to be rid of him. “I’ll do it, but not until I’ve received the check.” “Thank you, my friend. I’ll drop around with the paperwork tomorrow night.” “No, that’s not possible,” said Pat. “I’m working nights this month. You’d better make it tomorrow afternoon.” “You won’t be | casting, “for hors d‘oeuvres gelée de saumon sauvage et caviar impérial en aigre doux, which is wild salmon slivers and imperial caviar in a delicate jelly with sour cream and zucchini drizzled with dill vinegar. Also we have cuisses de grenouilles … la purée d’herbes … soupe, fricassée de chanterelles et racines de persil, which are pan-fried frogs’ legs in a parsley purée, fricassee of chanterelles and parsley roots. For the main course we have escalope de turbot, which is a poached fillet of turbot on a watercress purée, lemon sabayon, and a Gewürztraminer sauce. And, of course, everything that is on the menu can be recommended.” I felt full even before he had finished the descriptions. Christabel appeared to be studying the menu with due diligence. She pointed to one of the dishes, and the maître smiled approvingly. Duncan leaned across and asked if I had selected anything yet. “Consommé and the duck will suit me just fine,” I said without hesitation. “Thank you, sir,” said the maître. “How would you like the duck? Crispy, or perhaps a little underdone?” “Crispy,” I replied, to his evident disapproval. “And monsieur?” he asked, turning to Duncan. “Caesar salad and a rare steak.” The maître d’ retrieved the menus and was turning to go as Duncan said, “Now, let me tell you all about my idea for a novel.” “Would you care to order some wine, sir?” asked another waiter, who was carrying a large red leather book with golden grapes embossed on its cover |
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 4156.72 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. |