brendan_oconnor_ai brendan_oconnor_ai-2005 brendan_oconnor_ai-2005-15 knowledge-graph by maker-knowledge-mining
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Introduction: Here it is! Still need to read the book. I’m a little bothered by people proclaiming it to be the first application of economic principles to social questions — hasn’t social economics been around for decades? — but the spirit and approach is right.
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same-blog 1 1.0 15 brendan oconnor ai-2005-07-04-freakonomics blog
Introduction: Here it is! Still need to read the book. I’m a little bothered by people proclaiming it to be the first application of economic principles to social questions — hasn’t social economics been around for decades? — but the spirit and approach is right.
2 0.10546765 203 brendan oconnor ai-2014-02-19-What the ACL-2014 review scores mean
Introduction: I’ve had several people ask me what the numbers in ACL reviews mean — and I can’t find anywhere online where they’re described. (Can anyone point this out if it is somewhere?) So here’s the review form, below. They all go from 1 to 5, with 5 the best. I think the review emails to authors only include a subset of the below — for example, “Overall Recommendation” is not included? The CFP said that they have different types of review forms for different types of papers. I think this one is for a standard full paper. I guess what people really want to know is what scores tend to correspond to acceptances. I really have no idea and I get the impression this can change year to year. I have no involvement with the ACL conference besides being one of many, many reviewers. APPROPRIATENESS (1-5) Does the paper fit in ACL 2014? (Please answer this question in light of the desire to broaden the scope of the research areas represented at ACL.) 5: Certainly. 4: Probabl
3 0.10190622 2 brendan oconnor ai-2004-11-24-addiction & 2 problems of economics
Introduction: This is my idea based off of Bernheim and Rangel’s model of addict decision-making . It’s a really neat model; it manages to relax rationality to allow someone to do something they don’t want to do because they’re addicted to it. [Rationality assumes a nice well-ordered set of preferences; this model hypothesizes as distinction between emotional "liking" and cognitive, forward "wanting" that can conflict.] The model is mathematically tractable, it can be used for public welfare analysis, and to top it off — it’s got neuroscientific grounding! It appears to me there are two big criticisms of the economics discipline’s assumptions. One of course is rationality. The second has to do with the perfect structure of the market and environment that shapes both preferences and the ability to exercise them. One critique is about social structure: consumers are not atomistic individual units, but rather exchange information and ideas along networks of patterned social relations. (Socia
Introduction: I was planning to write some WordNet lookup code tonight. But instead I’ve learned of too many intersecting things. First, there are a zillion things to do this weekend ( hooray flavorpill ): Picasso and American Art exhibit continuing at SFMOMA . I saw it very briefly last weekend but want some more. And Doug claims there’s an interesting photography exhibit there too. Reading from We Don’t Need Another Wave: Dispatches from the Next Generation of Feminists , a fascinating looking book I’ve seen many times in the bookstores around here. By that I mean at least Modern Times (the neat Mission bookstore) and the Anarchist Collective Bookstore (out on the Haight). And the reading is at Modern Times, just down the street from my house! Amazing. Tomorrow at 7:30. Since anarchists were just mentioned, fortuitously there also appears: the Bay Area Anarchist Bookfair this Saturday and Sunday! Speakers and books down by Golden Gate Park, oh my. Can’t say I’m a ra
5 0.083467782 1 brendan oconnor ai-2004-11-20-gintis: theoretical unity in the social sciences
Introduction: Herbert Gintis thinks it’s time to unify the behavioral sciences. Sociology, economics, political science, human biology, anthropology and others all study the same thing, but each is based on different incompatible models of individual human behavior. There seems to be evidence that new developments have the potential to offer a more unifying theory. Evolutionary biology should be the basis of understanding much of human behavior. Rational choice and game theoretic frameworks are finding greater acceptance beyond economics; in the meantime, other fields need to absorb sociology’s emphasis on socialization — that people do things or understand the world in a way taught by society. The human behavioral sciences are still rife with many smaller inconsistencies; for example, according to Gintis, only anthropolgists look at the influence of culture across groups, but only sociologists look at culture within groups. Gintis’ ultimate goal is to have a common baseline from which each disci
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same-blog 1 0.99201161 15 brendan oconnor ai-2005-07-04-freakonomics blog
Introduction: Here it is! Still need to read the book. I’m a little bothered by people proclaiming it to be the first application of economic principles to social questions — hasn’t social economics been around for decades? — but the spirit and approach is right.
2 0.56942463 2 brendan oconnor ai-2004-11-24-addiction & 2 problems of economics
Introduction: This is my idea based off of Bernheim and Rangel’s model of addict decision-making . It’s a really neat model; it manages to relax rationality to allow someone to do something they don’t want to do because they’re addicted to it. [Rationality assumes a nice well-ordered set of preferences; this model hypothesizes as distinction between emotional "liking" and cognitive, forward "wanting" that can conflict.] The model is mathematically tractable, it can be used for public welfare analysis, and to top it off — it’s got neuroscientific grounding! It appears to me there are two big criticisms of the economics discipline’s assumptions. One of course is rationality. The second has to do with the perfect structure of the market and environment that shapes both preferences and the ability to exercise them. One critique is about social structure: consumers are not atomistic individual units, but rather exchange information and ideas along networks of patterned social relations. (Socia
3 0.49119863 38 brendan oconnor ai-2006-06-03-Neuroeconomics reviews
Introduction: Here are two great reviews, from 2003 then 2005. 1) PLoS Biology: Economy of the Mind nicely reviews the field and many interesting experiments. One annoyance: They need to say “Banburismus” is more commonly known as Bayesian learning. (Banbury, England was a city near Bletchley Park they got their paper from when doing Bayesian statistical codebreaking of the Enigma cipher in World War II. Read the story here in MacKay’s excellent free online textbook .) Thanks to neurodudes for the PLoS link. 2) Neuroeconomics: How neuroscience can inform economics is written by the leaders of the field, advocating their approach. I like the detail and their careful descriptions of how cognitive neuroscience findings can enhance our understanding of economic phenomena. Also, the second is useful to read since it’s the target of criticism by the more recent The case for mindless economics , which I view as an empire-strikes-back sort of paper. I’m waiting for Part III of this s
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Introduction: Today I received my copy of Beautiful Data , a just-released anthology of articles about, well, working with data. Lukas and I contributed a chapter on analyzing social perceptions in web data. See it here. After a long process of drafting, proofreading, re-drafting, and bothering the publishers under rather sudden deadlines, I’ve resolved to never use graphics again in anything I write :) Here’s our final figure, a k-means clustering of face photos via perceived social attributes (social concepts/types ? with exemplars ?): I just started reading the rest of the book and it’s very fun. Peter Norvig ‘s chapter on language models is gripping. (It does word segmentation, ciphers, and more, in that lovely python-centric tutorial style extending his previous spell correction article .) There are also chapters by many other great researchers and practitioners (some of whom you may have seen around this blog or its neighborhood) like Andrew Gelman , Hadley Wickham ,
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Introduction: PHD Comics: Humanities vs. Social Sciences
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1 0.96884674 128 brendan oconnor ai-2008-11-28-Calculating running variance in Python and C++
Introduction: It’s fairly obvious that an average can be calculated online, but interestingly, there’s also a way to calculate a running variance and standard deviation. Read all about it here . I’m playing around with the Netflix Prize data of 100 million movie ratings, and a huge problem is figuring out how to load and calculate everything in memory. I’m having success with NumPy , the numeric library for Python, because it compactly stores arrays with C/Fortran binary layouts. For example, 100 million 32-bit floats = 100M * 4 = 400MB of memory, which is manageable. And it’s much easier to play around interactively in ipython / matplotlib rather than write C++ for everything. Unfortunately, the simple ways to calculate variance on an array of that size create wasteful intermediate data structures as long as the original array. >>> mean( (x-mean(x)) ** 2 ) # two intermediate structures >>> tmp=x-mean(x); tmp**=2; mean(tmp) # one intermediate structure That’s an e
same-blog 2 0.89403188 15 brendan oconnor ai-2005-07-04-freakonomics blog
Introduction: Here it is! Still need to read the book. I’m a little bothered by people proclaiming it to be the first application of economic principles to social questions — hasn’t social economics been around for decades? — but the spirit and approach is right.
3 0.29445764 198 brendan oconnor ai-2013-08-20-Some analysis of tweet shares and “predicting” election outcomes
Introduction: Everyone recently seems to be talking about this newish paper by Digrazia, McKelvey, Bollen, and Rojas ( pdf here ) that examines the correlation of Congressional candidate name mentions on Twitter against whether the candidate won the race. One of the coauthors also wrote a Washington Post Op-Ed about it. I read the paper and I think it’s reasonable, but their op-ed overstates their results. It claims: “In the 2010 data, our Twitter data predicted the winner in 404 out of 435 competitive races” But this analysis is nowhere in their paper. Fabio Rojas has now posted errata/rebuttals about the op-ed and described this analysis they did here. There are several major issues off the bat: They didn’t ever predict 404/435 races; they only analyzed 406 races they call “competitive,” getting 92.5% (in-sample) accuracy, then extrapolated to all races to get the 435 number. They’re reporting about in-sample predictions, which is really misleading to a non-scientific audi
4 0.29159865 131 brendan oconnor ai-2008-12-27-Facebook sentiment mining predicts presidential polls
Introduction: I’m a bit late blogging this, but here’s a messy, exciting — and statistically validated! — new online data source. My friend Roddy at Facebook wrote a post describing their sentiment analysis system , which can evaluate positive or negative sentiment toward a particular topic by looking at a large number of wall messages. (I’d link to it, but I can’t find the URL anymore — here’s the Lexicon , but that version only gets term frequencies but no sentiment.) How they constructed their sentiment detector is interesting. Starting with a list of positive and negative terms, they had a lexical acquisition step to gather many more candidate synonyms and misspellings — a necessity in this social media domain, where WordNet ain’t gonna come close! After manually filtering these candidates, they assess the sentiment toward a mention of a topic by looking for instances of these positive and negative words nearby, along with “negation heuristics” and a few other features. He describ
5 0.27153382 154 brendan oconnor ai-2009-09-10-Don’t MAWK AWK – the fastest and most elegant big data munging language!
Introduction: update 2012-10-25 : I’ve been informed there is a new maintainer for Mawk, who has probably fixed the bugs I’ve been seeing. From: Gert Hulselmans [The bugs you have found are] indeed true with mawk v1.3.3 which comes standard with Debian/Ubuntu. This version is almost not developed the last 10 years. I now already use mawk v1.3.4 maintained by another developer (Thomas E. Dickey) for more than a year on huge datafiles (sometimes several GB). The problems/wrong results I had with mawk v1.3.3 sometimes are gone. In his version, normally all open/known bugs are fixed. This version can be downloaded from: http://invisible-island.net/mawk/ update 2010-04-30 : I have since found large datasets where mawk is buggy and gives the wrong result. nawk seems safe. When one of these newfangled “Big Data” sets comes your way, the very first thing you have to do is data munging: shuffling around file formats, renaming fields and the like. Once you’re dealing with hun
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