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Tag: social networks

Dear Humans, Diverse Social Networks are the Answer

In biology, it is clear that access to more genes leads to greater overall health. This is true because it allows for a greater likelihood that a genetic defect can be compensated by a gene from a different pool. This is the reason that inbreeding leads to more genetic diseases. This same phenomenon exists in social science. Complex social networks are healthier than more narrow (constrained) ones. Dr. Amar Dhand of the Brigham and Women’s Hospital’s Department of Neurology has, for example, shown that people are more likely to get to the emergency room in time to receive a clot busting therapy for stroke if they are part of a more complex, rather than constrained, social network.

The probable reason for this effect is the diversity of ideas that are available in the complex social networks is greater than in the narrow ones. Despite these advantages, human beings tend to resist diversity, depending instead on a competing drive to create cliques and clubs.   In Arlie Russell Hochschild’s book, Strangers in Their Own Land, she attempts to understand what she sees as a paradox.   Why do people vote in manners that seem to be contrary to their own self interest? In fact this is not a paradox, but rather simply a competition between two deeply ingrained human traits; one biological and the other sociological.

The phenomenon of professional burnout is a case in point. It is generally defined as a sense of cynicism, depersonalization and ineffectiveness. Some believe that we are in the midst of an epidemic of burnout, affecting as many as half of medical doctors, for example. The causes of burnout are protean, but at the core of the problem is the perception of unfairness; that one is the subject of a form of bias or prejudice whereby certain resources are unfairly distributed by a powerful force, such as the employer or the government. Any individual or group may be subject to this perception. Much of the conflict that is being expressed around the world can be understood as an analogue to professional burnout, in other words, caused at its root by a perception of unfairness. So what is perception and from where does it arise?

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The Case For Traveling to the Center of Our Social Networks

James FowlerMuch has been made of David Lazer’s finding that Google’s Flu Trends tracker seriously missed the mark in its measurement of flu activity for 2012-2013—and in previous years, too.

For those who don’t know, Flu Trends monitors Google search behaviors to identify regions where searches related to flu-like symptoms are spiking.In spite of Flu Trend’s notable misstep, Lazer still believes in the power of marrying health and social data.

In discussing the results of his study, he has maintained Google Flu is “a terrific” idea—one that just needs some refining. I agree.And, earlier this month, Nicholas Christakis, several other colleagues, and I—with funding from the Robert Wood Johnson Foundation—published a new method offering one such refinement.

Our paper shows that, in a given social network (in this study’s case, Twitter), a sample of its most connected, central individuals can hold significant predictive power.

We call this potentially powerful group of individuals a “sensor group.”

By finding and monitoring the tweets of a sensor group, we can catch—and sometimes even predict—the outbreak of contagious information early on. That detection edge could improve how we track the outbreak of disease epidemics, the rise of certain terms or phrases, or shifts in political sentiment.

Whereas Flu Trends relies on a relatively static, proprietary “dictionary” of flu-related search terms based on average Google search habits, the sensor method taps into what is really happening in social networks in real time.

By drawing on language being used by a sensor group—such as mentions of an emergent symptom or a popular newly coined name for a disease—Google could gain insight into what their dictionary might be missing.Sampling both the average Googler’s behavior and that of the exceptionally connected social network user can paint a much fuller picture of whatever landscape we are interested in tracking. We can more accurately see how it looks now—and how it could look in the near future.

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