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Transportation in Contemporary Society: A Complex Systems Approach [Via MIT World]
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Year: 2011
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Six Degrees of Marbury v. Madison : A Sink Based Visualization [v2]
The visualization above is something we are calling the “six degrees” of Marbury v. Madison. It was originally produced for use in our paper Distance Measures for Dynamic Citation Networks. Due to space considerations, we ended up leaving it on the cutting room floor. However, the visual is designed to highlight the idea of a “sink.”
Sinks are one of the core concepts which we outline in Distance Measures for Dynamic Citation Networks, 389 Physica A 4201 (October 1 2010). Looking through the prism of a citation network, sinks are the root to which a given legal concept, academic idea or patent based innovation can be drawn. From each citation in a non-sink node, it is possible to trace the chains of citations back to their root (which we call a sink). In the visualization above, the root or sink node is the famed United States Supreme Court decision Marbury v. Madison. Starting from the center and working out to the edge, the first ring are cases that directly cite Marbury v. Madison. The next ring are cases which cite cases that cite Marbury v. Madison. The next ring are cases which cite cases which cases that cite Marbury v. Madison and so on…
Anyway, one of the major contributions of our Distance Measures for Dynamic Citation Networks paper is that it allows us to use these sinks to create pairwise distance/similarity measure between the ith and jth unit. In this instance, the units in this directed acyclic network are the ith and jth decisions of the United States Supreme Court.
Now, it is important to note cases contain many citations and thus can be oriented relative to many different sinks. So, even if a case can be traced to the Marbury sink – this does not preclude it from being traced to other sinks as well. Also, it is possible to construct a variety of mathematical functions to characterize the sink based distance between units. For instance, the importance of a sink might decay as its shortest path length increases. An alternative measure might weight the importance of each sinks by the number of unique ancestors shared between nodes i and j that are descended from a given sink of interest. Indeed, many fine-grained choices are possible but they require justification drawn from the given substantive problem.
As mentioned above, this method has potential applications including tracing the spread of technological innovation in patent citations or the spread of ideas in a set of academic articles. However, given our primary interest surrounds the judicial citations, we are working on the follow up to the “sinks” paper. In this follow up paper, we hope to carry these and other ideas forward into a definitive community detection method for judicial citation networks.
To preview, at least two major dynamics must be considered in any null model for community detection. First, case-to-case citations can help contribute to the fractal nature of legal systems. In other words, we are pretty far from any sort of gaussian null model. However, this is easy enough to confront with an alternative null — some highly skewed distribution (i.e. power law or power law with a cutoff, etc.)
Here is the difficult part — the cross fertilization of legal concepts. This is a time evolving network where ideas are referenced/imported from otherwise unrelated or previously unrelated domains. The examples of cross-fertilization are numerous. One of my personal favorite non-SCOTUS examples is the use of the tort doctrine of “trespass to chattels” in the context of web scraping.
Anyway, we hope to have more to come on the topic of SCOTUS community detection in the weeks and months to come. In the meantime, please check out a Dynamic 3D Hi Definition United States Supreme Court Visualization.
Oyez @ Chicago Kent Releases Free OyezToday App for IPhone
Kudos to Jerry Goldman, the other folks at the Oyez Project as well as the Chicago-Kent College of Law for making this free resource available to the public!
From the description: “OYEZTODAY at IIT Chicago-Kent College of Law offers you the latest information and media on the current business of the Supreme Court of the United States. OYEZTODAY provides: easy-to-grasp abstracts for every case granted review, timely and searchable audio of oral arguments + transcripts, and up-to-date summaries of the Court’s most recent decisions including the Court’s full opinions. You will have access to all this information on your iPhone with the ability to share reactions on Facebook, Twitter, or by email. (Recordings of opinion announcements from the bench will follow when the Court releases these files to the National Archives at the start of the Court’s next Term). Chicago-Kent is proud to provide this free service to enhance the public’s understanding of the Supreme Court and current legal controversies.”
Network Structure of Production [From PNAS]
From the abstract: “Complex social networks have received increasing attention from researchers. Recent work has focused on mechanisms that produce scale-free networks. We theoretically and empirically characterize the buyer–supplier network of the US economy and find that purely scale-free models have trouble matching key attributes of the network. We construct an alternative model that incorporates realistic features of firms’ buyer–supplier relationships and estimate the model’s parameters using microdata on firms’ self-reported customers. This alternative framework is better able to match the attributes of the actual economic network and aids in further understanding several important economic phenomena.”
Complex Systems: A Survey
From the abstract: “A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a short survey and an annotated bibliography of resources for those interested in learning about complex systems.” [By Mark E.J. Newman – Submitted to Amer. J. Physics]
Complex systems is a relatively young subject area and one that is evolving rapidly, but there are nonetheless a number of general references, including books and reviews, that bring together relevant topics in a useful way. ” The paper then has recommended materials on major topics relevant to the study of complex systems including:
- Lattices and Networks
- Dynamical Systems (including Chaos & Fractals)
- Discrete Dynamics and Cellular Automata
- Scaling and Criticality
- Adaptation and Game Theory
- Information Theory
- Computational Complexity
- Agent-Based Modeling
“Classic examples of complex systems include condensed matter systems, ecosystems, the economy and financial markets, the brain, the immune system, granular materials, road traffic, insect colonies, flocking or schooling behavior in birds or fish, the Internet, and even entire human societies.”
Salman Khan: Let’s Use Video to Reinvent Education [ TED 2011 ]
“In 2004, Salman Khan, a hedge fund analyst, began posting math tutorials on YouTube. Six years later, he has posted more than 2.000 tutorials, which are viewed nearly 100,000 times around the world. In this TED 2011 Talk, Salman talks about how and why he created the remarkable Khan Academy, a carefully structured series of educational videos offering complete curricula in math and, now, other subjects. He shows the power of interactive exercises, and calls for teachers to consider flipping the traditional classroom script — give students video lectures to watch at home, and do “homework” in the classroom with the teacher available to help.”
This offers a pretty interesting alternative model for education delivery. It is worth checking out!
Deb Roy: The Birth of a Word [TED 2011]
This is one of the better TED Talks I have seen to date. It is definitely worth watching!
From the abstract: MIT researcher Deb Roy wanted to understand how his infant son learned language — so he wired up his house with videocameras to catch every moment (with exceptions) of his son’s life, then parsed 90,000 hours of home video to watch “gaaaa” slowly turn into “water.” Astonishing, data-rich research with deep implications for how we learn.
For an interesting related talk, check out Patricia Kuhl– The linguistic genius of babies (TEDxRanier).
How to Grow a Mind: Statistics, Structure, and Abstraction [via Science]
From the abstract: “In coming to understand the world—in learning concepts, acquiring language, and grasping causal relations—our minds make inferences that appear to go far beyond the data available. How do we do it? This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?”
Shameless Family Promotion — Clear Blue @ SXSW 2011
Rock / Paper / Scissors – Man v. Machine (as t→∞ you are not likely to win) [via NY Times]
From the site … “A truly random game of Rock-Paper-Scissors would result in a statistical tie with each player winning, tying and losing one-third of the time … However, people are not truly random and thus can be studied and analyzed. While this computer won’t win all rounds, over time it can exploit a person’s tendencies and patterns to gain an advantage over its opponent.
Computers mimic human reasoning by building on simple rules and statistical averages. Test your strategy against the computer in this rock-paper-scissors game illustrating basic artificial intelligence. Choose from two different modes: novice, where the computer learns to play from scratch, and veteran, where the computer pits over 200,000 rounds of previous experience against you.”
Time to dust off your random seed / pseudorandom number generators … good luck!
Some Papers We Have Been Reading [March 2011 Edition]
Social Structure of Facebook Networks (By Amanda L. Traud, Peter J. Mucha & Mason A. Porter)
Practicing Theory: Legal Education for the Twenty-First Century (By Larry Ribstein)
How Judges Decide: A Multidimensional Empirical Typology of Judicial Styles in the Federal Courts (By Corey Rayburn Yung)
Brain Scans as Evidence: Truths, Proofs, Lies, and Lessons (By Francis X. Shen & Owen D. Jones)
Small but Slow World: How Network Topology and Burstiness Slow Down Spreading (By M. Karsai, M. Kivela, R. K. Pan, K. Kaski, J. Kertesz, A.L. Barabasi & J. Saramaki)
Abandoning Law Reports for Official Digital Case Law (By Peter W. Martin)
Scaling of Prosocial Behavior in Cities (By Samuel Arbesman & Nicholas A. Christakis)
Empiricism and the Rising Incidence of Coauthorship in Law (By Tom Ginsburg & Tom Miles)
