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Eeeeeee. Photo: Wenliang Chen

The science of the Internet’s virality—the psychological and neurological understanding of which stories people share and why they share them (and why BuzzFeed exists)—has come up with the three key components of a well-traveled story: cats, cats and babies. Actually, it’s a little more complex than that, writes John Tierney in The New York Times. But stories that are shared widely online do have a few things in common.

For one, the most shared stories evoke strong emotions, with positive feelings of awe and joy trumping feelings of disgust or outrage. People tend “to share articles that were exciting or funny, or that inspired negative emotions like anger or anxiety, but not articles that left them merely sad. They needed to be aroused one way or the other, and they preferred good news to bad. The more positive an article, the more likely it was to be shared.”

What else do widely shared stories share? They remind us of other people. Let’s say your friend really loves dolphins. Well, you’ll probably want to send them that super emotional story you just saw about dolphins. The key is not necessarily that you care about the story so much as that you think the person you’re sending it to will care about the story.

But, says Tierney, people are still super self-centered. People get really excited when they “are sharing information about their favorite subject of all: themselves.”

“In fact, the study showed, it’s so pleasurable that people will pass up monetary rewards for the chance to talk about themselves.”

The internet, says Tierney, runs counter to the “if it bleeds it leads” mantra of the traditional press. Though wars and plagues and trauma are important, they’re also heavy emotional burdens that people may not want to put on their friends. Instead, it’s funny pictures of corgis all the way down. (Look at their little legs!)

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Deborah Blum, a journalist who specializes in poisons, first picked up on the disturbing frequency of pet poisonings after setting up a Google alert on poisoning events and accumulating more 300 news stories on poisoned pets over the course of one year. Then, she began receiving unsolicited emails from pet owners who had lost animals. When she began looking into it, she also stumbled upon forums where pet haters who wanted to rid themselves of their neighbor’s pesky dog or cat would post messages such as:

I want to know the best way to kill next door neighbors’ cat, with out them suspecting anything. Its her closest pet and I need it to be gone. It kills bird and it comes in my back yard. Is there any way to poision it or dart it?

Last year when Blum wrote a piece for PLoS Blogs on the topic, the comment section turned into a bragging forum on the best ways to kill a messy cat or poison a barking dog.

So why do people chose to harm others’ pets? From the hundreds of news stories, comments and emails Blum has combed through, she explains on Wired, she found a few culprits that cropped up again and again:

• Common crime. For example, a California burglar recently poisoned two dogs in order to break into a house.
• Neighbors or people we know. Estranged spouses or exes may kill an animal as a form of revenge upon their former flame. Others do it to terrorize or send a threatening message to enemies. (Think of the horse head scene from The Godfather.) Neighbors often poison pets in order to quiet a noisy dog or stop a cat from digging up the rose garden or stalking the birds.
• Random cruelty. Still others chose to poison pets for the heck of it, Blum writes, leaving poison-laced treats in public parks.

As Women in Crime Ink writes, the link between animal cruelty and crime is well documented in scientific literature. Killing a noisy dog or an irksome cat is only a step or two removed from carrying out similar violence upon fellow humans. So there is ample reason for anyone who suspects their pet was poisoned to feel nervous.

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Anyone who’s spent any time on the internet is familiar with trolls. From politics to sports to science, trolls take pleasure in bashing a story from every possible angle. Science is no exception, and recent research shows that when it comes to science news, the trolls are winning.

The University of Wisconsin reports on a recent study that tried to quantify just how much of an impact trolls could have on a reader. Basically, the researchers showed comments on a blog post about nanotechnology to study participants. They surveyed their users pre-existing ideas about nanotechnology and measured how those ideas might change based on the blog and the comments beneath it. What they found was that negative comments, regardless of their merit, could sway readers. The University of Wisconsin writes:

For rapidly developing nanotechnology, a technology already built into more than 1,300 consumer products, exposure to uncivil online comments is one of several variables that can directly influence the perception of risk associated with it.

“When people encounter an unfamiliar issue like nanotechnology, they often rely on an existing value such as religiosity or deference to science to form a judgment,” explains Ashley Anderson, a postdoctoral fellow in the Center for Climate Change Communication at George Mason University and the lead author of the upcoming study in the Journal of Computer Mediated Communication.

At Mother Jones, Chris Mooney puts it this way:

The researchers were trying to find out what effect exposure to such rudeness had on public perceptions of nanotech risks. They found that it wasn’t a good one. Rather, it polarized the audience: Those who already thought nanorisks were low tended to become more sure of themselves when exposed to name-calling, while those who thought nanorisks are high were more likely to move in their own favored direction. In other words, it appeared that pushing people’s emotional buttons, through derogatory comments, made them double down on their preexisting beliefs.

In the context of the psychological theory of motivated reasoning, this makes a great deal of sense. Based on pretty indisputable observations about how the brain works, the theory notes that people feel first, and think second. The emotions come faster than the “rational” thoughts—and also shape the retrieval of those thoughts from memory. Therefore, if reading insults activates one’s emotions, the “thinking” process may be more likely to be defensive in nature, and focused on preserving one’s identity and preexisting beliefs.

So without a background in nanotechnology—or whatever other subject you might be reading about—an emotionally charged comment is going to trigger your brain to act far before a logical explanation of how something works. And emotionally charged comments are a troll’s weapon of choice.

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The “broken window theory” has had its day. This criminological theory, which argues that keeping urban environments neat and tidy deters would-be criminals, first popped up in social science in 1969, with a famous experiment detailing the fates of two different cars left out on the street in the Bronx and in Palo Alto with their hoods open and license plates removed. (Spoiler: the car in Palo Alto fared better—until the researcher broke its window, after which it was quickly stripped down.) The theory gained popularity through the ’80s, when The Atlantic first covered it, and ’90s, when New York City used it to design policing strategy, before, in 2000, it helped journalist Malcolm Gladwell make his career with The Tipping Point. The book earned the author whopping $1 million advance, and introduced to the theory to a much wider audience—many readers remember  most vividly the broken window section of Gladwell’s best-seller.

Turns out, however, that the broken window theory doesn’t really apply that well to reality. New research shows that New York City’s historic decline in crime rates during the 1990s cannot be attributed to CompState, the NYC police department’s dynamic approach to crime, introduced in 1994, that included carrying out operations in accordance with the broken window theory. The crime decline has nothing to do with enhanced enforcement of misdemeanors, the research published in Justice Quarterly by New York University professor David Greenberg reports, nor is there any link between arrests in misdemeanors and drops in felony charges, including robberies, homicides and assaults.

“While the 1990s drop in felonies is undeniable, what remains unsolved is the cause, or causes, behind this significant change in New York City’s crime rates,” Greenberg said in a statement.

In addition, neither the number of police officers per capita nor the rate of prison sentences doled out to criminals turned out to be related to a reduction in violent crime. To arrive at these findings, Greenberg examined crime data across NYC’s 75 precincts from 1988 to 2001. During this time, crime rates fell nearly uniformly across the city. (Incidentally, Los Angeles, San Diego and other major cities underwent a similar shift in crime during this time.)

His analysis found no relationship between the decline in violence crime and CompStat or any of the other actions inspired by broken window theory. While violent crime decreased over the 13 year period, Greenberg found, misdemeanors increased in all but 11 precincts, invalidating the theory’s basis. Felonies, on the other hand, dropped consistently across the city, independently of a shrinking police force, imprisonment rates or enforcement levels, which varied greatly around the five boroughs.

“While many may point to greater enforcement of lower-level offenses as a factor in curbing more serious crimes, the data simply don’t support this conclusion,” Greenberg said. He added that he has no idea why the crime dropped—only that it had nothing to do with broken windows.

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The news is often dubbed the “first rough draft of history,” the first crack at making sense of the struggles and triumphs of our time. A new artificial intelligence engine, however, might be able harvest those drafts to figure out the future. By using advanced computational techniques to parse through two decades of New York Times stories and other resources, Microsoft researcher Eric Horvitz and Technion-Israel Institute of Technology scientist Kira Radinsky, think they might be able to identify the underlying connections between real-world events and predict what will happen next.

The trick is that many newsworthy events—riots, disease outbreaks—says the BBC, are preceded by other other less dramatic news stories. But, by digging through such a vast wealth of stories, these otherwise overlooked associations can be pulled out.

In their research paper, the two scientists say that using a mixture of archived news reports and real-time data, they were able to see links between droughts and storms in parts of Africa and cholera outbreaks.

For example in 1973 the New York Times published news of a drought in Bangladesh, and in 1974 it reported a cholera epidemic.

Following reports of another drought in the same country in 1983, the newspaper again reported cholera deaths in 1984.

“Alerts about a downstream risk of cholera could have been issued nearly a year in advance,” wrote researchers Eric Horvitz, director of Microsoft Research, and Kira Radinsky, PhD student at Technion-Israel Institute of Technology.

This model doesn’t necessarily mean that, for Bangladesh, drought will always lead to cholera. But, by viewing the occurrences with an eye to the future, an impending drought could be a sign to Bangladeshi water managers to keep a closer eye on their treatment programs, or for healthcare workers to be wary of an outbreak.

Similar links between drought and cholera, says MIT’s Technology Review, were identified for Angola.

In similar tests involving forecasts of disease, violence, and a significant numbers of deaths, the system’s warnings were correct between 70 to 90 percent of the time.

Techniques like this one are used in science all the time. Neural networks, machine learning and artificial intelligence approaches have helped YouTube discover—without human intervention—what cats are and have helped paleontologists speed up the fossil hunt. Because they can analyze vast swaths of data, computers are particularly well-suited for pulling out some of the non-obvious trends that permeate history. MIT’s Tom Simonite:

Many things about the world have changed in recent decades, but human nature and many aspects of the environment have stayed the same, Horvitz says, so software may be able to learn patterns from even very old data that can suggest what’s ahead. “I’m personally interested in getting data further back in time,” he says.

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