Dr. Peter Erdi is one of the leading scholars studying the path of innovation as revealed through the U.S. Patent Citation network.  Above is his most recent talk – Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

For some of his additional work please see:
Patent Citation Networks Revisited: Signs of a Twenty-First Century Change?, North Carolina Law Review (2009).
Modeling Innovation by a Kinetic Description of the Patent Citation System, Physica A (2007)
Law and the Science of Networks: An Overview and an Application to the ‘Patent Explosion’, Berkeley Technology Law Journal (2007).

[Note: Load Time for the Video above is a bit slow]

Many of you are aware of my obsession (here) (here) (here) with fractals, power law distributions, etc. and their role in understanding a variety of phenomena.  In this spirit, I recently came across this video on MIT World from the late Benoît B. Mandelbrot.  It is well worth the watch – enjoy!

From the abstract: “The authors study a simple model of an asset market with informed and non-informed agents. In the absence of non-informed agents, the market becomes information efficient when the number of traders with different private information is large enough. Upon introducing non-informed agents, the authors find that the latter contribute significantly to the trading activity if and only if the market is (nearly) information efficient. This suggests that information efficiency might be a necessary condition for bubble phenomena—induced by the behavior of non-informed traders—or conversely that throwing some sands in the gears of financial markets may curb the occurrence of bubbles.”  [ HT: Paul Kedrosky ]

Abstract: “The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system’s entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network’s degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.”

From this week’s issue of Science comes Filling the Light Pipe by David J. Richardson. This is an important article highlighting a serious challenge facing the both the scientific and policy community.

From the abstract: “It has been a landmark year for the field of optical telecommunications, with the award of the 2009 Nobel Prize to Charles Kao for his insight in the mid-1960s that the future of communications lay in single-mode silica-based optical fibers (1) as well as the 50th anniversary of the first demonstration of the laser—both key technologies responsible for the development of the global-scale communications networks of today (2). Recently, however, a growing realization has emerged within the telecommunications industry that the end of the phenomenal growth in optical fiber communication capacity is within sight. At this year’s Optical Fiber Communication Conference (OFC 2010), several groups reported results within a factor of 2 of the ultimate capacity limits of existing optical fiber technology. Without radical innovation in our physical network infrastructure—that is, improvements in the key physical properties of transmission fibers and the optical amplifiers that we rely on to transmit data over long distances—we face what has been widely referred to as a “capacity crunch” that could severely constrain future Internet growth, as well as having social and political ramifications.”

[HT to Paul Kedrosky]

An exciting new paper entitled “A Taxonomy of Networks” by Jukka-Pekka Onnela, Daniel J. Fenn, Stephen Reid, Mason A. Porter, Peter J. Mucha, Mark D. Fricker & Nick S. Jones just hit the Physics arXiv.  I wanted to flag it for anyone who might be interested.

Here is the abstract: “The study of networks has grown into a substantial interdisciplinary endeavor across the natural, social, and information sciences. Yet there have been very few attempts to investigate the interrelatedness of the different classes of networks studied by different disciplines. Here, we introduced a framework to establish a taxonomy of networks from various origins. The provision of this family tree not only helps understand the kinship of networks, but also facilitates the transfer of empirical analysis, theoretical modeling, and conceptual developments across disciplinary boundaries. The framework is based on probing the mesoscopic properties of networks, an important source of heterogeneity for their structure and function. Using our method, we computed a taxonomy for 752 individual networks and a separate taxonomy for 12 network classes. We also computed three within-class taxonomies for political, fungal, and financial networks, and found them to be insightful in each case.”

This summer in the Complex Systems Advanced Academic Workshop we are devoting attention to information theory.  In collecting some materials about Claude Shannon, I came across the above video and thought I would share it with others.  Here is the description … “Considered the founding father of the electronic communication age, Claude Shannon’s work ushered in the Digital Revolution. This fascinating program explores his life and the major influence his work had on today’s digital world through interviews with his friends and colleagues.”

Tomorrow is the first day of presentations at NetSci2010. Our paper will presented in AM Network Measures Panel.  Anyway, for those interested in leveraging network science to study the dynamics of large social and physical systems — the conference promises a fantastic lineup of speakers. Check out the program!

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