Tagged with “network theory” (5)

  1. BBC Radio 4 - In Our Time, Complexity

    Melvyn Bragg and guests discuss complexity theory.

    Melvyn Bragg and his guests discuss complexity and how it can help us understand the world around us. When living beings come together and act in a group, they do so in complicated and unpredictable ways: societies often behave very differently from the individuals within them. Complexity was a phenomenon little understood a generation ago, but research into complex systems now has important applications in many different fields, from biology to political science. Today it is being used to explain how birds flock, to predict traffic flow in cities and to study the spread of diseases.


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  2. Duncan Watts: Using the Web to do Social Science

    Social science is often concerned with the emergence of collective behavior out of the interactions of large numbers of individuals; but in this regard it has long suffered from a severe measurement problem - namely that interactions between people are hard to measure, especially at scale, over time, and at the same time as observing behavior.

    In this talk, Duncan will argue that the technological revolution of the Internet is beginning to lift this constraint. To illustrate, he will describe four examples of research that would have been extremely difficult, or even impossible, to perform just a decade ago:

    Using email exchange to track social networks evolving in time Using a web-based experiment to study the collective consequences of social influence on decision making Using a social networking site to study the difference between perceived and actual homogeneity of attitudes among friends Using Amazon’s Mechanical Turk to study the incentives underlying ‘crowd sourcing’ Although internet-based research still faces serious methodological and procedural obstacles, Duncan proposes that the ability to study truly ‘social’ dynamics at individual-level resolution will have dramatic consequences for social science.


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  3. Linked: Networks from Biology to the World Wide Web

    September 27, 2005

    Albert-Laszlo Barabasi, a Notre Dame University physics professor, explores the relationships of various kinds of complex networks from cells and epidemics, to the World Wide Web, with a bit of ‘Six Degrees of Kevin Bacon’ in between. In accessible language and with humor, Barabasi explains how seemingly unrelated types of networks, for example corporations, social networks, living organisms, are more similar than previously thought. Albert-Laszlo Barabasi is the author of Linked: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life.


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  4. Burst Interview with Albert-László Barabási

    In this interview, I talk with Albert-László Barabási, author of Bursts: The Hidden Pattern Behind Everything We Do.

    Barabási has been on the forefront of research into network theory. His first book Linked was about the connections. His new book Bursts is about the dynamics of how we live. He says we need to move from a model which emphasizes averages and random behavior to one that is represented by short periods of intense activity followed by longer lulls. Applications have already been seen in the diagnosis of depression and the movement of money.


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  5. 6 Degrees of Separation

    Episode three of A Further Five Numbers, the BBC radio series presented by Simon Singh.

    Six is often treated as 2x3, but has many characteristics of its own. Six is also the "pivot" of its divisors (1+2+3=6=1x2x3) and also the centre of the first five even numbers: 2, 4, 6, 8, 10. Six seems to have a pivoting action both mathematically and socially. How is it that everyone in the world can be linked through just six social ties? As Simon discovers, the concept of “six degrees of separation” emerged from a huge postal experiment conducted by the social psychologist Stanley Milgram in 1967. Milgram asked volunteers to send a package by mail to one of a hundred people chosen at random. But they could only send mail to people they knew on first name terms.

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