Tag Archives: social networks

Mapping the social network of American colleges by status

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The Chronicle of Higher Education has a fascinating story and interactive area that shows social networks among American universities and colleges:

Each year colleges submit “comparison groups” to the U.S. Department of Education to get feedback on how their institution stacks up in terms of finances, enrollment, and other measures tabulated in the Integrated Postsecondary Education Data System. The groups sometimes represent a college’s actual peers but more often reveal their aspirations.

The Chronicle analyzed the relationships of nearly 1,600 four-year colleges that make up those groups to map out the power players in higher education.

The typical college selected a comparison group of 16 colleges with a higher average SAT score and graduation rate than its own, lower acceptance rate, and larger endowment, budget, and enrollment.

The eight Ivy League colleges among them chose only 12 institutions outside their own number as peers—not surprisingly, often including the University of Chicago, the Massachusetts Institute of Technology, and Stanford University.

So it looks like colleges themselves act like high school students applying to college as laid out by sociologist Mitchell Stevens in Making a Class: they want to improve their own status by attaching themselves to a higher status institution.

It would take some time to figure this out based on entering different college names but here would be some intriguing queries that could be answered by the interactive graphic:

1. Which colleges are most aspirational?

2. Which college are the best judges of their own level, meaning that they select institutions that also select them?

3. What are the institutions that act as bridges, meaning they join together networks of different kinds of colleges or regions of colleges?

4. Are there any colleges that actually underestimate their own status by choosing institutions “below” them?

Using Twitter to predict when you will get sick with 90% accuracy

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A new study uses tweets in New York City to predict when a user will get sick – and does so with 90% accuracy.

Using 4.4 million tweets with GPS location from over 630,000 users in New York City, Sadilek and his team were able to predict when an individual would get sick with the flu and tweet about it up to eight days in advance of their first symptoms. Researchers found they could predict said results with 90 percent accuracy.

Similar to Google’s Flu trends, which uses “flu” search trends to pinpoint where and how outbreaks are spreading, Sadilek’s system uses an algorithm to differentiate between alternative definitions of the word ‘sick.’ For example, “My stomach is in revolt. Knew I shouldn’t have licked that door knob. Think I’m sick,” is different from “I’m so sick of ESPN’s constant coverage of Tim Tebow.”

Of course, Sadilek’s system isn’t an exhaustive crystal ball. Not everyone tweets about their symptoms and not everyone is on Twitter. But considering New York City has more Twitter users than any other city in the world, the Big Apple is as good as a place as any for this study.

While one could look at this and marvel at the power of Twitter, I think the real story here is about two things: (1) the power of big data and (2) the power of social networks that Twitter harnesses. If you have people volunteering information about their lives, access to the data, and information about who users are connected to, you can do things that would have been very difficult even ten years ago.

It is interesting that this study was conducted in New York City where there is a high percentage of Twitter users. How good are predictions in cities with lower usage rates? Are we headed toward a world where public health requires people to report on their health so that outbreaks can be contained or quelled?

Sociologist: 70% of murders in two high-crime Chicago neighborhoods tied to social network of 1,600 people

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Social networks can be part of more nefarious activities: sociologist Andrew Papachristos looked at two high-crime Chicago neighborhoods and found that a majority of the murders involved a small percentage of the population.

Papachristos looked at murders that occurred between 2005 and 2010 in West Garfield Park and North Lawndale, two low-income West Side neighborhoods. Over that period, Papachristos found that 191 people in those neighborhoods were killed.

Murder occasionally is random, but, more often, he found, the victims have links either to their killers or to others linked to the killers. Seventy percent of the killings he studied occurred within what Papachristos determined was a social network of only about 1,600 people — out of a population in those neighborhoods of about 80,000.

Each person in that network of 1,600 people had been arrested at some point with at least one other person in the same network.

For those inside the network, the risk of being murdered, Papachristos found, was about 30 out of 1,000. In contrast, the risk of getting killed for others in those neighborhoods was less than one in 1,000.

On one hand, this isn’t too surprising, especially considering the prevalence of gangs. At the same time, these numbers of striking: if a resident is in this small network, their risk of being murdered jumps 3000%.

I would be interested to know how closely the Chicago Police have mapped social networks like these. Do they use special social network software that helps them visualize the network and see nodes? Indeed, the article suggests the police are doing something like this:

Now, he wants to tap the same social networking analysis techniques that Papachristos, the Yale sociologist, developed to identify potential shooting victims, only McCarthy wants to use it to identify potential killers.

Police brass will cross-reference murder victims and killers with their known associates — the people projected as most likely to be involved in future shootings.

“Hot people,” McCarthy calls them.

Those deemed most likely to commit violence will be targeted first: parolees and people who have outstanding arrest warrants.

McCarthy said his staff estimates there are 26,000 “hot people” living in Chicago.

It would also be worthwhile to see how effective such strategies are. This isn’t the first time that organizations/agencies have tried to identify at-risk individuals. So how effective is it in the long run?

A call to “begin creating synthetic sociology”

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Two academics call for “synthetic sociology”:

Well, it’s time we begin creating synthetic sociology. Along with Nicholas Christakis, I recently laid out the potential for this new field:

We wanted to see if this could be done in humans. Like crabs, humans have specific kinds of behavior that can be predicted, in groups. To harness this, we created a survey on Amazon’s Mechanical Turk, surveying lots of people at once.

We asked a couple hundred people to complete a string of 1’s and 0’s, and asked them to make it “as random as possible.” As it happens, people are fairly bad at generating random numbers—there is a broad human tendency to suppose that strings must alternate more than they do. And what we found in our Mechanical Turk survey was exactly this: Predictably, people would generate a nonrandom number. For example, faced with 0, 0, there was about a 70 percent chance the next number would be 1.

From this single behavioral quirk, it is theoretically possible to construct a way in which a group of humans can act as what is known as a logic gate in computer science. By running such a question through a survey of enough people, and feeding those results to other people, you can turn them into what computer scientists call a “NOR” gate—a tool to take two pieces of binary input and yield consistent answers. And with just a handful of NOR gates, you can make a binary adder, a very simple computing device that can add two numbers together.

What this means is that, given sufficient numbers of people, and their willingness to answer questions about random bits, we can re-deploy humans for a purpose they were not intended, namely to act as a kind of computer—doing anything from adding two bits to running Microsoft Word (albeit really, really slowly).

On one hand, it sounds like we are far from using these methods to have humans finish complicated tasks yet, on the other hand, this continues to build upon research about social networks and how information and other traits can be passed along and built on in a group of people. As these academics suggest, we have come some distance in recent decades in understanding and modeling human behavior and advances are likely to continue to come in the near future.

This also isn’t the first time that I have heard of social scientists using Amazon’s Mechanical Turk for studies. For a relatively small amount of money, researchers can find a willing group of participants for experiments or other tasks.

Facebook’s Data Science Team running experiments

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Facebook’s Data Science Team of 12 researchers is working with all of its data (900 million users worth) and running experiments:

“Recently the Data Science Team has begun to use its unique position to experiment with the way Facebook works, tweaking the site-the way scientists might prod an ant’s nest-to see how users react… So [Eytan Bakshy] messed with how Facebook operated for a quarter of a billion users. Over a seven-week period, the 76 million links that those users shared with each other were logged. Then, on 219 million randomly chosen occasions, Facebook prevented someone from seeing a link shared by a friend. Hiding links this way created a control group so that Bakshy could assess how often people end up promoting the same links because they have similar information sources and interests.

“He found that our close friends strongly sway which information we share, but overall their impact is dwarfed by the collective influence of numerous more distant contacts-what sociologists call “weak ties.” It is our diverse collection of weak ties that most powerfully determines what information we’re exposed to.”

But if that sounds a little creepy, it shouldn’t. Well, not too creepy, because these kinds of experiments aren’t designed to influence us, but rather understand us. The piece continues:

“Marlow says his team wants to divine the rules of online social life to understand what’s going on inside Facebook, not to develop ways to manipulate it. “Our goal is not to change the pattern of communication in society,” he says. “Our goal is to understand it so we can adapt our platform to give people the experience that they want.” But some of his team’s work and the attitudes of Facebook’s leaders show that the company is not above using its platform to tweak users’ behavior. Unlike academic social scientists, Facebook’s employees have a short path from an idea to an experiment on hundreds of millions of people.”

I think there is a lot of room to explore the world of weak ties on Facebook and similar websites. Just how much do friends of friends affect us? What is the impact of people a few ties along in our network? For example, the book Connected shows that traits like obesity and happiness are tied to network behavior which could be examined on Facebook.

I would guess some people may not like hearing this but there are at least three points in Facebook’s favor here:

1. They are not the only online company running such experiments. Google has been doing such things with search results for quite a while. Theoretically, these experiments could help create a better user experience.

2. People are voluntarily giving their data. I don’t think these companies have to explain that user’s data might be used in experiments…but perhaps I am wrong?

3. This is “Big Data” writ large. Facebook and others would love to be able to run randomized trials with this large group and with all of the information available to researchers.

Parents who share about their kid’s success may be engaging in a helpful networking strategy

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Sociologist Annette Lareau argues that parents who make their kid’s accomplishments known may be engaging in important networking activity:

Parents today are more anxious about the economy and their children’s futures than their predecessors, says University of Pennsylvania sociology professor Annette Lareau, and that can complicate the bragging versus sharing issue.

But she also points out that talking about your child’s extracurriculars is an effective networking strategy.

“It takes a lot of informal knowledge to have your kids in organized activities,” she says. You need to know about sign-up dates, carpool opportunities and how competitive, challenging or welcoming an activity will be.

“Mothers are very dependent on other mothers to share information,” Lareau says.

In this view, mothers and parents are sharing information about their own kids in order to build relationships with other parents as well as learn more information about social and community opportunities. Perhaps the bragging doesn’t haven’t to be overt but it is signalling to other parents about the abilities of their children and could lead to specialized information that could help their children even more. If you think your kid has special talents, then you would want to talk to other parents who have traveled similar paths and already some of the legwork.

More broadly, I wonder how much social networks are implicated in the Matthew Effect (“the rich get richer, the poor get poorer”), whether we are talking about children or people of different backgrounds and opportunities. It certainly plays a role but how much (i.e., could we put a percentage on it)?

A new world where weak social ties can spread videos like Kony 2012

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The Kony 2012 video has been watched over 65 million times on YouTube. While there has been much commentary about how the video lacks nuance, there is another interesting issue to consider: how exactly did it spread so quickly? One columnist suggests the sociological idea of weak ties provides some insights:

Many years ago, the Stanford sociologist Mark Granovetter published a seminal article in the American Journal of Sociology on the special role of “weak ties” in networks – links among people who are not closely bonded – as being critical for spreading ideas and for helping people join together for action.

An examination of the spread of the Kony video suggests that one weak tie in particular may have been critical in launching it to its present eminence. Her name is Oprah Winfrey and she tweeted: “Have watched the film. Had them on show last year” on 6 March, after which the graph of YouTube views of the video switches to the trajectory of a bat out of hell. Winfrey, it turns out, has 9.7 million followers on Twitter…

In this online world of weak ties, famous tweeters like Oprah Winfrey have more influence than they have ever had before. Even though television shows or movies might be larger cultural works, new developments like Twitter and Facebook allow anyone with some influence to reach a large number of people quickly. With Winfrey located closer to the middle of a global cultural network, her suggestion can resound throughout the world.

The same columnist also considers what might happen as the result of these weak ties. In other words, what does it matter that over 65 million people saw this video?

The really interesting question, though, is whether this kind of development will further ratchet up the pressure on democratic politicians. The last two decades have shown how 24/7 media coverage of foreign atrocities can lead western leaders to morally driven interventionism.

We’ll have to see how this plays out. The Kony video itself claims that these sorts of media efforts work as they already pushed the United States to send 100 military advisers to central Africa. Additionally, they say this happened “because the people demanded it.” But they also suggest their viral efforts are not enough: the video talks about targeting a collection of political and cultural leaders, “20 culture-makers and 12 policy-makers.” Take these figures, such as Oprah Winfrey or Condoleezza Rice, out of the campaign and would as many people, in the public or on Capitol Hill, pay attention? Could just the public put enough pressure on governments through social media or viral videos? Also, the video itself is quite a production (a number of people involved in making it, per the credits on the YouTube video) from an established organization. This is a little different from a 10 year making a video in her bedroom.

This is not to take away from the fact that this videos has reached a tremendous amount of people. But if we want to understand why all those people paid attention, the story is much more complicated. Mass numbers can have an influence but powerful people are more centrally located within social networks and have more influential ties. If Kony 2012 is going to have legs and lead to lasting change, weak ties may not be enough.

Trying to disprove Dunbar’s number on Facebook

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One writer tried to disprove Dunbar’s number on Facebook but found that Dunbar was correct after all:

Not for Dunbar, apparently. He was looking for individual interactions. Well, I thought, if that’s all it takes to disprove Dunbar’s number, then that’s what I’ll do: I’ll write personal letters to every one of my 2,000 Facebook friends…

I only made it through 1,000 of my 2,000 Facebook friends. But that was enough. My experiment’s outcome was crystal clear: Dunbar’s number kicked my ass.

In trying to disprove Dunbar’s number, I actually proved it. I proved that even if you’re aware of Dunbar’s number, and even if you set aside a chunk of your life specifically to broaden your social capital, you can only maintain so many friendships. And “so many” is fewer than 200.

Writing my Facebook “friends” had taken over my time. I was breaking plans with real friends to send meaningless messages to strangers. Some of the strangers didn’t respond, and many of those who did respond only confirmed Dunbar’s theory.

Quick examples: When I wrote A. F., a Malaysian magician, he responded: “hey rick i think you might’ve sent me this message by mistake lol.” And when I wrote A.D., a friend of a friend, and asked how things were going, she replied, “Sorrx but do i know you?:)”

The question I want to ask next: so did this writer lose friends over the course of this? If so, was it because the friends did the dropping or the writer decided to pare down his friends list?

While Facebook allows people to have expanded “friendship” networks, it is interesting to consider what would actually happen if someone tried to activate these networks. For example, the friend you once had in third grade and are now are Facebook friends with: what can you reasonably ask that person to do? Respond to a quick message you send them? Catch up with you and talk about what has happened in your lives since you last talked? Help you out of a tough spot? Join a cause you are interested in? Alert you to a job opening that would help you? My guess is that most of these online relationships rarely can be counted on even though they may have a semi-permanent status on Facebook. If this is the case, then perhaps you have hundreds upon hundreds of friends on Facebook but only 150 or so (Dunbar’s number) can be counted as actionable relationships.

This is not necessarily bad for Facebook: perhaps that 150 friends can shift rapidly over time meaning one week someone is a close friend while several months later it is someone else. Or perhaps you don’t actually know which of your friends is part of the 150 until you engage in deeper interaction. To have more social capital, it is helpful to have broader social networks that you can attempt to utilize. Without those connections at all, it is more difficult to find information or produce change.

Sociologist: social media is not socially isolating

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In a debate over the merits and consequences of living alone, sociologist Keith Hampton argues that social media is not socially isolating:

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Sociologist explains that one type of mass hysteria is behind cases in upstate New York

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A recent set of odd medical cases in one New York town has prompted news sources to look for explanations. One sociologist suggests the high school students are experiencing one type of mass hysteria:

Most doctors and experts believe that the students are suffering from mass sociogenic illness, also known as mass hysteria. In these cases, psychological symptoms manifest as physical conditions.

Sociologist Robert Bartholomew, author of several books on mass hysteria including The Martians Have Landed: A History of Media-Driven Panics and Hoaxes, explained to Discovery News that “there are two main types of contagious conversion disorder. The most common in Western countries is triggered by extreme, sudden stress; usually a bad smell. Symptoms typically include dizziness, headaches, fainting and over-breathing, and resolve within about a day.”

In contrast, Bartholomew said, “The LeRoy students are experiencing the rarer, more serious type affecting muscle motor function and commonly involves twitching, shaking, facial tics, difficulty communicating and trance states. Symptoms appear slowly over weeks or months under exposure to longstanding stress, and typically take weeks or months to subside.”

Mass hysteria cases are more common than people realize and have been reported all over the world for centuries.

Read the rest of the story for four more interesting stories of mass hysteria. These sorts of stories pop up every once in a while: a few people claim to be ill from smelling something but authorities can’t find any issue.

I’ve seen Bartholomew quoted in a few news stories about this mystery illness. I would be interested to hear how he thinks you can defuse this situation; how do you stop mass hysteria? Is it best to focus on reducing the stress of the people experiencing the illness or is it better to split up the group of those experiencing the illness to try to limit the “mass” part of the condition?

Also, do we have any studies of what takes place within a community that is experiencing this as opposed to studying the situations afterward? What is it like for the other students and their families in this high school?

Third, what kind of stress sets this off?

Fourth, is there something about the social networks between those who are ill that matter or the particular institutional setting that people are in (i.e., close quarters for long hours)?