Tag Archives: viral

Idea Soup

Rudeness Goes Viral

We know intuitively, anecdotally and through scientific study that aggressive behavior can be transmitted to others through imitation. The famous Bobo doll experiment devised by researchers at Stanford University in the early 1960s, and numerous precursors, showed that subjects given an opportunity to observe aggressive models later reproduced a good deal of physical and verbal aggression substantially identical with that of the model. In these studies the model was usually someone with a higher social status or with greater authority (e.g., an adult) than the observer (e.g., a child).

Recent updates to these studies now show that low-intensity behaviors such as rudeness can be as equally contagious as more intense behaviors like violence. Fascinatingly, the contagion seems to work equally well even if the model and observer are peers.

So, keep this in mind: watching rude behaviors leads us to be rude to others.

From Scientific American:

Flu season is nearly upon us, and in an effort to limit contagion and spare ourselves misery, many of us will get vaccinated. The work of Jonas Salk and Thomas Francis has helped restrict the spread of the nasty bug for generations, and the influenza vaccine is credited with saving tens of thousands of lives. But before the vaccine could be developed, scientists first had to identify the cause of influenza — and, importantly, recognize that it was contagious.

New research by Trevor Foulk, Andrew Woolum, and Amir Erez at the University of Florida takes that same first step in identifying a different kind of contagious menace: rudeness. In a series of studies, Foulk and colleagues demonstrate that being the target of rude behavior, or even simply witnessing rude behavior, induces rudeness. People exposed to rude behavior tend to have concepts associated with rudeness activated in their minds, and consequently may interpret ambiguous but benign behaviors as rude. More significantly, they themselves are more likely to behave rudely toward others, and to evoke hostility, negative affect, and even revenge from others.

The finding that negative behavior can beget negative behavior is not exactly new, as researchers demonstrated decades ago that individuals learn vicariously and will repeat destructive actions.  In the now infamous Bobo doll experiment, for example, children who watched an adult strike a Bobo doll with a mallet or yell at it were themselves abusive toward the doll.  Similarly, supervisors who believe they are mistreated by managers tend to pass on this mistreatment to their employees.

Previous work on the negative contagion effect, however, has focused primarily on high-intensity behaviors like hitting or abusive supervision that are (thankfully) relatively infrequent in everyday life.  In addition, in most previous studies the destructive behavior was modeled by someone with a higher status than the observer. These extreme negative behaviors may thus get repeated because (a) they are quite salient and (b) the observer is consciously and intentionally trying to emulate the behavior of someone with an elevated social status.

…

To examine whether this sensitivity impacts social behavior, Foulk’s team conducted another study in which participants were asked to play the part of an employee at a local bookstore.  Participants first observed a video showing either a polite or a rude interaction among coworkers.  They were then asked to respond to an email from a customer.  The email was either neutral (e.g., “I am writing to check on an order I placed a few weeks ago.”), highly aggressive (e.g., “I guess you or one of your incompetent staff must have lost my order.”), or moderately rude (I’m really surprised by this as EVERYBODY said you guys give really good customer service???).

Foulk and colleagues again found that prior exposure to rude behavior creates a specific sensitivity to rudeness. Notably, the type of video participants observed did not affect their responses to the neutral or aggressive emails; instead, the nature of those emails drove the response.  That is, all participants were more likely to send a hostile response to the aggressive email than to neutral email, regardless of whether they had previously observed a polite or rude employee interaction.  However, the type of video participants observed early in the study did affect their interpretation of and response to the rude email.  Those who had seen the polite video adopted a benign interpretation of the moderately rude email and delivered a neutral response, while those who had seen the rude video adopted a malevolent interpretation and delivered a hostile response.  Thus, observing rude behaviors, even those committed by coworkers or peers, resulted in greater sensitivity and heightened response to rudeness.

Read the entire article here.

Idea Soup

Pre-Twittersphere Infectious Information

While our 21st century always-on media and information sharing circus pervades every nook and cranny of our daily lives, it is useful to note that pre-Twittersphere, ideas and information did get shared. Yes, useful news and even trivial memes did go viral back in the 18oos.

From Wired:

The story had everything — exotic locale, breathtaking engineering, Napoleon Bonaparte. No wonder the account of a lamplit flat-bottom boat journey through the Paris sewer
went viral after it was published — on May 23, 1860.

At least 15 American newspapers reprinted it, exposing tens of thousands of readers to the dank wonders of the French city’s “splendid system of sewerage.”

Twitter is faster and HuffPo more sophisticated, but the parasitic dynamics of networked media were fully functional in the 19th century. For proof, look no further than the Infectious Texts project, a collaboration of humanities scholars and computer scientists.

The project expects to launch by the end of the month. When it does, researchers and the public will be able to comb through widely reprinted texts identified by mining 41,829 issues of 132 newspapers from the Library of Congress. While this first stage focuses on texts from before the Civil War, the project eventually will include the later 19th century and expand to include magazines and other publications, says Ryan Cordell, an assistant professor of English at Northeastern University and a leader of the project.

Some of the stories were printed in 50 or more newspapers, each with thousands to tens of thousands of subscribers. The most popular of them most likely were read by hundreds of thousands of people, Cordell says. Most have been completely forgotten. “Almost none of those are texts that scholars have studied, or even knew existed,” he said.

The tech may have been less sophisticated, but some barriers to virality were low in the 1800s. Before modern copyright laws there were no legal or even cultural barriers to borrowing content, Cordell says. Newspapers borrowed freely. Large papers often had an “exchange editor” whose job it was to read through other papers and clip out interesting pieces. “They were sort of like BuzzFeed employees,” Cordell said.

Clips got sorted into drawers according to length; when the paper needed, say, a 3-inch piece to fill a gap, they’d pluck out a story of the appropriate length and publish it, often verbatim.

Fast forward a century and a half and many of these newspapers have been scanned and digitized. Northeastern computer scientist David Smith developed an algorithm that mines
this vast trove of text for reprinted items by hunting for clusters of five words that appear in the same sequence in multiple publications (Google uses a similar concept for its Ngram viewer).

The project is sponsored by the NULab for Texts, Maps, and Networks at Northeastern and the Office of Digital Humanities at the National Endowment for the Humanities. Cordell says the main goal is to build a resource for other scholars, but he’s already capitalizing on it for his own research, using modern mapping and network analysis tools to explore how things went viral back then.

Counting page views from two centuries ago is anything but an exact science, but Cordell has used Census records to estimate how many people were living within a certain distance of where a particular piece was published and combined that with newspaper circulation data to estimate what fraction of the population would have seen it (a quarter to a third, for the most infectious texts, he says).

He’s also interested in mapping how the growth of the transcontinental railroad — and later the telegraph and wire services — changed the way information moved across the country. The animation below shows the spread of a single viral text, a poem by the Scottish poet Charles MacKay, overlaid on the developing railroad system. The one at the very bottom depicts how newspapers grew with the country from the colonial era to modern times, often expanding into a territory before the political boundaries had been drawn.

Read the entire article here.

Image: Courtesy of Ryan Cordell / Infectious texts project. Thicker lines indicate more content-sharing between 19th century newspapers.

Idea Soup

Why Do Some Videos Go Viral, and Others Not?

Some online videos and stories are seen by tens or hundreds of millions, yet others never see the light of day. Advertisers and reality star wannabes search daily for the secret sauce that determines the huge success of one internet meme over many others. However, much to the frustration of the many agents to the “next big thing”, several fascinating new studies point at nothing more than simple randomness.

[div class=attrib]From the New Scientist:[end-div]

WHAT causes some photos, videos, and Twitter posts to spread across the internet like wildfire while others fall by the wayside? The answer may have little to do with the quality of the information. What goes viral may be completely arbitrary, according to a controversial new study of online social networks.

By analysing 120 million retweets – repostings of users’ messages on Twitter – by 12.5 million users of the social network, researchers at Indiana University, Bloomington, learned the mechanisms by which memes compete for user interest, and how information spreads.

Using this insight, the team built a computer simulation designed to mimic Twitter. In the simulation, each tweet or message was assigned the same value and retweets were performed at random. Despite this, some tweets became incredibly popular and were persistently reposted, while others were quickly forgotten.

The reason for this, says team member Filippo Menczer, is that the simulated users had a limited attention span and could only view a portion of the total number of tweets – as is the case in the real world. Tweets selected for retweeting would be more likely to be seen by a user and re-posted. After a few iterations, a tweet becomes significantly more prevalent than those not retweeted. Many users see the message and retweet it further.

“When a meme starts to get popular it displaces other memes; you start to pay attention to the popular meme and don’t pay attention to other things because you have only so much attention,” Menczer says. “It’s similar to when a big news story breaks, you don’t hear about other things that happened on that day.”

Katherine Milkman of the University of Pennsylvania in Philadelphia disagrees. “[Menczer’s study] says that all of the things that catch on could be truly random but it doesn’t say they have to be,” says Milkman, who co-authored a paper last year examining how emotions affect meme sharing.

Milkman’s study analysed 7000 articles that appeared in the New York Times over a three-month period. It found that articles that aroused readers’ emotions were more likely to end up on the website’s “most emailed” list. “Anything that gets you fired up, whether positive or negative, will lead you to share it more,” Milkman says.

[div class=attrib]Read the entire article after the jump.[end-div]

[div class=attrib]Image: Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets is a book by Nassim Nicholas Taleb. Courtesy of Wikipedia.[end-div]