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Deadly Cross

  by James Patterson


(about 331 pages)
82,649
total words
of all the books in our library
40.93%
vividness
of all the books in our library
7.07%
passive voice
of all the books in our library
2.37%
all adverbs
of all the books in our library
0.72%
ly-adverbs
of all the books in our library
1.65%
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
text, the most recent one from Christopher to Kay the day before they died. Quote: ‘You won’t believe what I’m onto. If I’m right, big, big boost in profile. Can’t wait to see you tonight.’ “A big boost in profile,” Mahoney said. “Did she reply?” “Yes, with an emoji blowing him a kiss.” You won’t believe what I’m onto. Though I wondered about what Christopher had been onto, I couldn’t let go of the fact they both seemed to have been using the dark web. I asked, “What was the motivation for them to use Tor? I mean, there had to be a reason that they would want to use heavily encrypted methods of communicating in the first place.” The computer scientist was quiet, then said, “I see where you’re going. One or both of them might have believed that they were under electronic surveillance.” “Were they?” Mahoney asked. “I was going to ask you the same thing,” Rawlins replied. “Not that I’m aware of. But who knows? I’ll have to contact the NSA.” I said, “Can’t you tell from the cloud accounts, Keith? Wouldn’t there be digital markers somewhere that would suggest they were under surveillance and, if so, by who?” Rawlins said, “I can look, but if there is, don’t be surprised if I set off some alarms.” “I look forward to that, actually. It’s about time we shake some trees, see what falls out.” BREE HAD WORN HER DRESS blues for Billie’s funeral and did not have saw water glistening on tire tracks. “More recent.” We drove through the woods into fields that must once have been full of cotton plants but were now overgrown with bramble and thistle. It was a deeply disturbing feeling to imagine the backbreaking hours that enslaved people had spent in those fields. The plantation house appeared. In its day, from the way Kay had described it to me, her paternal grandmother’s mansion must have been breathtaking, a sprawling antebellum manor finished in alabaster white and forest-green trim with a covered porch that wrapped around the entire house and a well-tended flower garden on the front lawn. Now, however, the neglect showed everywhere. The alabaster finish was speckled and splashed with mold and peeling away in big strips. Parts of the porch roof had caved in. Kudzu choked the front columns and the entire porch railing. Tentacles and shrouds of the creeping vine had already reached the upper floors, where birds were flashing in and out of dark windows with broken, jagged glass. “This is where Kay Willingham, queen of the DC socialites, is buried?” I said. WE DROVE TOWARD THE DECREPIT plantation house and saw that a road had been cleared and maintained beyond it. Mahoney continued down the road through more overgrown fields and pine thickets. We were well out of sight of the mansion when I spotted headstones up on a knoll ahead. “Stop there,” I said. Mahoney pulled over by a stone path leading up to the knoll

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 1652.98 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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