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Month: November 2011

Predicting the votes of judges

Here is a (short) and interesting paper that uses an innovative approach to predict the votes of the US Supreme Court: Successful attempts to predict judges’ votes shed light into how legal decisions are made and, ultimately, into the behavior and evolution of the judiciary. Here, we investigate to what extent it is possible to make predictions of a justice’s vote based on the other justices’ votes in the same case. For our predictions, we use models and methods that have been developed to uncover hidden associations between actors in complex social networks. We show that these methods are more accurate at predicting justice’s votes than forecasts made by legal experts and by algorithms that take into consideration the content of the cases. We argue that, within our framework, high predictability is a quantitative proxy for stable justice (and case) blocks, which probably reflect stable a priori attitudes toward the law. We find that U.S. Supreme Court justice votes are more predictable than one would expect from an ideal court composed of perfectly independent justices. Deviations from ideal behavior are most apparent in divided 5–4 decisions, where justice blocks seem to be most stable. Moreover, we find evidence that justice predictability decreased during the 50-year period spanning from the Warren Court to the Rehnquist Court, and that aggregate court predictability has been significantly lower during Democratic presidencies. More broadly, our results show that it is possible to use methods developed for the analysis of complex social networks to quantitatively investigate…

What makes a video go viral?

Internet Marketing expert Dr Brent Coker claims to have developed an algorithm that can predict which ad movies will go viral on YouTube. I don’t plan a career move to advertising but was nevertheless intrigued by the claim from a research methods & design perspective. Unfortunately, there is very little information available (yet?) and what information is available makes me a bit skeptical about the reliability of the conclusion. Still, Dr Coker’s approach might make for a nice discussion in the context of a Research Design course since it touches upon a question students can relate to, and raises various issues from operationalization to theory specification to theory testing. In short, according to Dr Coker, “there are four elements that need to be in place for a branded movie to become viral: (1) congruency, (2) emotive strength, (3) network-involvement ratio, and (4) paired meme synergy”. Congruency is the consistency of the video’s theme with brand knowledge. Disgust and fear, for example, imply powerful emotive strength. The network-involvement ratio refers to how relevant the message is to the seeded network. The last element ‘paired meme synergy’ means that certain memes are effective when paired with certain other memes. “For example, impromptu entertainment acts appeared to work when paired with ‘Eyes Surprise’. When paired with ‘bubblegum nostalgia’, the … pair doesn’t work. Anticipation works with Voyeur, but not on its own. And so forth.” As I said, there is not much information available on the research design, but from what I can gather, the predictive algorithm is based on an inductive approach: analyze movies that did go…


The art of science 2011 Individuals who feel entitled are more inclined to perceive dull tasks as a waste of their time I wonder whether you can infer from the fact the someone is often bored that (s)he has an inflated sense of entitlement Do cows align with the Earth’s magnetic field?Major disagreements among scientists; the main issue seems to be what counts as quality data – perhaps not surprisingly given that the data is cattle photographed from space. Retired US generals outraged that Congress effectively categorizes pizza as a vegetable in school lunch programs

Game theory and real estate negotiations

Here is a puzzle: You meet a real estate agent for a property you are interested in. The house has an asking prize and you haven’t made any offers yet. The realtor mentions casually that she has just had an offer for the house which she has rejected. Would you ask what the offer was? Would the realtor tell you? Is it a fair question to ask? (obviously, the realtor is under no obligation to reveal the truth value of the rejected offer and there is no way for me to verify the answer).

Here is a formalized description of the problem: the Seller adn the Buyer can be each of two types – High or Low.  High Buyers and Sellers prefer High Deal to No Deal no Low Deal, and Low Buyers and Sellers prefer High Deal to Low Deal to No Deal. First, the Seller announces whether she has rejected a Very low or a Moderate offer. If a Moderate offer has been (announced as) rejected, the Buyer can make either a High offer (which all Sellers accept) or No offer which ends the game. If a Very low offer has been (announced as) rejected, the Buyer can make a Low offer, No offer or a High offer (the latter two end the game). If a Low offer has been made, the Seller can either Accept or Reject it. In the case of rejection the Buyer can make a High offer or No offer – both actions end the game. Here is the game tree.

Essentially, by making an announcement that she has rejected a Moderate offer the Seller credibly commits to reject any Low offers. Importantly, Buyers suffer a cost from a rejected offer (which is realistic given the costs of the compulsory technical surveys one has to do before an offer). There is no penalty for a late deal (no time discounting). The game is of two-sided incomplete information – neither the Buyers nor the Sellers know the type of the opponent. So the questions:

1) Should you ask what the rejected offer was?
2) Should the realtor (the Seller) tell you?
3) Would the answer (announcement) of the Seller be informative?
4) Does the Seller do better under this game or a game with no signal (announcement)?
5) Does the Buyer do better under this game or a game with no signal?
6) Is this game Pareto-improving under any circumstances?

My answers are after the fold.


Alcohol linked to breast cancer (hm, do they sufficiently control for confounding variables?) Scientists more likely to have autistic kids? Probably not, but worth checking the entire Nature issue devoted to autism Ben Goldacre summarizes his experience  writing on bad science Fatty foods as addictive as cocaine  (no, that doesn’t mean cocaine is fine)

Foreign media exposure and democratization

This paper [ungated; longer version] has it all: a  design based on a ‘natural experiment’, recently declassified East German public opinion surveys, and a counterintuitive result – exposure to West German TV increased support for the the East German communist regime. Here is the abstract: In this case study of the impact of West German television on public support for the East German communist regime, we evaluate the conventional wisdom in the democratization literature that foreign mass media undermine authoritarian rule. We exploit formerly classified survey data and a natural experiment to identify the effect of foreign media exposure using instrumental variable estimators. Contrary to conventional wisdom, East Germans exposed to West German television were more satisfied with life in East Germany and more supportive of the East German regime. To explain this surprising finding, we show that East Germans used West German television primarily as a source of entertainment. Behavioral  data on regional patterns in exit visa applications and archival evidence on the reaction of the East German regime to the availability of West German television corroborate this result. The ‘randomization’ is based on the fact that the penetration of West German TV in East Germany was determined by topographical features. The area around Dresden is the main one which had no access so it serves to anchor the comparisons. The effect sizes reported in the empirical analysis are not great – the different models and estimators show a positive effect of exposure to West German TV in the range…