[press release] Penn Professor Shows How ‘Spontaneous’ Social Norms Emerge

Thinking this still does not shed any light on “wisdom of crowds” vs rumor mongering.  Consensus isn’t always a matter of truth finding.  Critical thinking skills are important!
Great insight, tho’.

From the 2 February 2015 Penn State press release by Katherine Unger Baillie

Fifteen years ago, the name “Aiden” was hardly on the radar of Americans with new babies. It ranked a lowly 324th on the Social Security Administration’s list of popular baby names. But less than a decade later, the name became a favorite, soaring into the top 20 for five years and counting.

While some may attribute its popularity to a “Sex in the City” character, a new study led by the University of Pennsylvania’s Damon Centola provides a scientific explanation for how social conventions – everything from acceptable baby names to standards of professional conduct – can emerge suddenly, seemingly out of nowhere, with no external forces driving their creation.

The research used an original Web-based experiment to test whether and how large populations come to consensus. The findings have implications for everything from understanding why different regions of the country have distinct words for the same product — soda versus pop, for example — to explaining how norms regarding civil rights gained widespread traction in the United States.

The paper, “The Spontaneous Emergence of Conventions,” will appear in the Early Edition of theProceedings of the National Academy of Sciences the week of Feb. 2.

“Our study explains how certain ideas and behaviors can gain a foothold and, all of a sudden, emerge as big winners,” Centola said. “It is a common misconception that this process depends upon some kind of leader, or centralized media source, to coordinate a population.  We show that it can depend on nothing more than the normal interactions of people in social networks.”

Centola is an associate professor in Penn’s Annenberg School for Communication and the School of Engineering and Applied Science and is director of the Network Dynamics Group at Penn. He partnered on the work with physicist Andrea Baronchelli, an assistant professor at City University London.

To understand how social norms arise, Centola and Baronchelli invented a Web-based game, which recruited participants from around the World Wide Web using online advertisements. In each round of the “Name Game,” participants were paired, shown a photograph of a human face and asked to give it a name. If both players provided the same name, they won a small amount of money. If they failed, they lost a small amount and saw their partner’s name suggestion. The game continued with new partners for as many as 40 rounds.

Though the basic structure of the game remained the same throughout the experiment, the researchers wanted to see whether changing the way that players interacted with one another would affect the ability of the group to come to consensus.

They began with a game of 24 players, each of whom was assigned a particular position within an online “social network.” The participants, however, weren’t aware of their position, didn’t know who they were playing with or even how many other players were in the game.

Centola and Baronchelli tested the effects of three different types of networks.

In the “geographical network” version, players interacted repeatedly with their four closest neighbors in a spatial neighborhood. In the “small world network” game, participants still played with only four other players, but the partners were chosen randomly from around the network. And in the “random mixing” version, players were not limited to four other partners, instead playing each new round with a new partner selected at random from all the participants.

As the games proceeded, the researchers observed clear patterns in people’s behavior that distinguished the different networks.

In the geographical and small world network games, participants easily coordinated with their neighbors, but they were not able to settle on one overall “winning” name for the population. Instead, a few competing names emerged as popular options: Sarah, Elena, Charlene and Julie all vying for dominance, for instance, with no global agreement.

 

[Press release] A simple intervention can make your brain more receptive to health advice

From the 2 February 2015 University of Pennsylvania press release

 

Emily Falk, Ph.D.

A new discovery shows how a simple intervention—self-affirmation – can open our brains to accept advice that is hard to hear.

“Self-affirmation involves reflecting on core values,” explained Emily Falk, the study’s lead author and director of the Communication Neuroscience Laboratory at University of Pennsylvania’s Annenberg School for Communication. Has your doctor ever told you to get more exercise?  Has your spouse ever suggested you eat healthier? Even though the advice comes from good intentions, most people feel defensive when confronted with suggestions that point out their weaknesses. Reflecting on values that bring us meaning can help people see otherwise threatening messages as valuable and self-relevant. “Our work shows that when people are affirmed, their brains process subsequent messages differently.”

…

Past studies have shown that brain activity in VMPFC during health messages can predict behavior change better than individuals’ own intentions, and this study sheds new light on why.  VMPFC is the brain region most commonly activated when participants think about themselves and when they ascribe value to ideas. The new results show that opening the brain in this way is a key pathway to behavior change.  “Understanding the brain opens the door to new health interventions that target this same pathway,” Falk noted.

“We were particularly interested in using self-affirmation to help people become more active because sedentary behavior is one of the biggest health threats faced by both Americans and people around the world,” said Falk.  Overly sedentary lifestyles are becoming a big problem; in some regions nearly 85 percent of an adult population leads an inactive lifestyle. This can cause multiple health problems, including poor heart health, diabetes, and cancer, just to name three. Increasing activity even small amount can have an important impact on both mental and physical health.

….

Psychologists have used self-affirmation as a technique to improve outcomes ranging from health behaviors in high risk patients to increasing academic performance in at risk youth, suggesting that the findings may be applicable across a wide range of interventions.  “Our findings highlight that something as simple as reflecting on core values can fundamentally change the way our brains respond to the kinds of messages we encounter every day,” Falk noted.  “Over time, that makes the potential impact huge.”

…

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[News] Scientists say tweets predict heart disease and community health — Tech News and Analysis

                                                                        Psychological Science / UPenn

 

Scientists say tweets predict heart disease and community health — Tech News and Analysis.

Excerpt from the 22 January 2015 article

University of Pennsylvania researchers have found that the words people use on Twitter can help predict the rate of heart disease deaths in the counties where they live. Places where people tweet happier language about happier topics show lower rates of heart disease death when compared with Centers for Disease Control statistics, while places with angry language about negative topics show higher rates.

The findings of this study, which was published in the journal Psychological Science, cut across fields such as medicine, psychology, public health and possibly even civil planning. It’s yet another affirmation that Twitter, despite any inherent demographic biases, is a good source of relatively unfiltered data about people’s thoughts and feelings,well beyond the scale and depth of traditional polls or surveys. In this case, the researchers used approximately 148 million geo-tagged tweets from 2009 and 2010 from more than 1,300 counties that contain 88 percent of the U.S. population.

(How to take full advantage of this glut of data, especially for business and governments, is something we’ll cover at our Structure Data conference with Twitter’s Seth McGuire and Dataminr’s Ted Bailey.)

What’s more, at the county level, the Penn study’s findings about language sentiment turn out to be more predictive of heart disease than any other individual factor — including income, smoking and hypertension. A predictive model combining language with those other factors was the most accurate of all.

That’s a result similar to recent research comparing Google Flu Trends with CDC data. Although it’s worth noting that Flu Trends is an ongoing project that has already been collecting data for years, and that the search queries it’s collecting are much more directly related to influenza than the Penn study’s tweets are to heart disease.

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