The Yahoo! News Political Dashboard has re-launched for the general election stretch run of the 2008 US Presidential election.
From the main map you can see the status of the election in every state according to either polls or Intrade prediction market odds. Hover your mouse over a state to see current numbers or click on a state to see historical trends. On the side, help you can see search trends, price blogs, story news, and demographic breakdowns at national and state levels.
You can also “create your own scenario” by picking who will win in every state. You can save and share your prediction and compare against markets, polls, history, or celebrities. More on ycorpblog.
In the markets view, states are colored either bright red or bright blue, regardless of how close the race is in that state. To see a visualization that blends colors to reflect the tightness of the race, see electoralmarkets.com.
Yahoo! News also offers a candidate badge that you can display on your blog declaring your choice. The badge features national-level polls, prediction markets, search buzz, and money raised.
NYCE Day is a gathering for people in the NYC metropolitan area with interests in auction algorithms, economics, game theory, e-commerce, marketing, and business to discuss common research problems and topics in a relaxed environment. The aim is to foster collaboration and the exchange of ideas.
If you haven’t played around with Yahoo! Pipes, I highly recommend it. It’s a usable and useful service that brings web mashups to the masses, making this favorite hacker pastime as easy as dragging objects around on the screen.
The easiest way to get started is to find an existing Pipe, clone it, and modify it as your own. Using this feature, I cloned my Obama map and in about one minute had a McCain map too.
Pipes uses a visual programming interface. The idea of “programming by picture” (I recall playing with one in the 1980s) never took hold as a mainstream tool. However, as a metaphor for mashups, where to goal is to chain together a number of sources and services, the visual approach seems exactly right. The implementation in a browser is a feat of ajaxian magic that I still find remarkable, even as Yahoo! and others are commoditizing the art. I imagine that even non-programmers should have little trouble constructing their own Pipes. Here is a screenshot of the source “code” for my Obama map:
Pipes has dozens of useful modules, including user input, Yahoo! Search, Flickr, and regular expressions.
You can embed the Pipe on your own website with a single line of javascript. I did this with my Obama and McCain campaign travel maps here. Or you can grab the output as an XML feed to use however you wish.
The icing on the cake for me is how Pipes — unlike so many other web sites, including some on Yahoo! — treats me and my Opera browser like adults:
(BTW, Pipes seems to work fine on Opera).
Unfortunately, Daniel Raffel, one of the key founders of Yahoo! Pipes, left Yahoo!. However, the team seems to be strong and continues to innovate, so I’m hopeful this fantastic service will continue to improve and thrive.
I joined the quantcast audience measurement service. It took about two minutes to sign up and initiate tracking. I’m impressed with the ease of use, the utility, and the inroads the company has made in the year or so since former Yahoo Mike Speiser first showed it to me.
I also joined the scribd document hosting service (“Youtube for documents”) and used it to embed a PDF in my previous post. Again, from signup to service took a matter of minutes. (I think scribd could be great for hosting my publications which are in need of both a content and interface update.)
Probably there’s some sort of business axiom here, probably already blogged and book-ed: the two minute rule of successful web services.
WeatherBill let’s you construct an enormous variety of insurance contracts related to weather. For example, the screenshot embedded below shows how I might have insured my vacation at the New Jersey shore:
For $42.62 I could have arranged to be paid $100 per day of rain during my vacation.
(I didn’t actually purchase this mainly because the US government insists that I am a menace to myself and should not be allowed to enter into such a dangerous gamble — more on this later. And as Dan Reeves pointed out to me, it’s probably not rational to do for small sums.)
WeatherBill is an example of the evolution of financial exchanges as they embrace technology.
WeatherBill can be thought of as expressive insurance, a financial category no doubt poised for growth and a wonderful example of how computer science algorithms are finally supplanting the centuries-old exchange logic designed for humans (CombineNet is another great example).
WeatherBill can also be thought of as a combinatorial prediction market with an automated market maker, a viewpoint I’ll expand on now.
On WeatherBill, you piece together contracts by specifying a series of attributes: date range, place, type of weather, threshold temperature or participation level, minimum and maximum number of bad-weather days, etc. The user interface is extremely well done: a straightforward series of adaptive menu choices and text entry fields guide the customer through the selection process.
This flexibility quickly leads to a combinatorial explosion: given the choices on the site I’m sure the number of possible contracts you can construct runs into the millions.
Once you’ve defined when you want to be paid — according to whatever definition of bad weather makes sense for you or your business — you choose how much you want to be paid.
Finally, given all this information, WeatherBill quotes a price for your custom insurance contract, in effect the maximum amount you will lose if bad weather doesn’t materialize. Quotes are instantaneous — essentially WeatherBill is an automated market maker always willing to trade at some price on any of millions of contracts.
Side note: On WeatherBill, you control the magnitude of your bet by choosing how much you want to be paid. In a typical prediction market, you control magnitude by choosing how many shares to trade. In our own prediction market Yoopick, you control magnitude by choosing the maximum amount you are willing to lose. All three approaches are equivalent, and what’s best depends on context. I would argue that the WeatherBill and Yoopick approaches are simpler to understand, requiring less indirection. The WeatherBill approach seems most natural in an insurance context and the Yoopick approach in a gambling context.
How does the WeatherBill market maker determine prices? I don’t know the details, but their FAQ says that prices change “due to a number of factors, including WeatherBill forecast data, weather simulation, and recent Contract sales”. Certainly historical data plays an important role — in fact, with every price quote WeatherBill tells you what you would have been paid in years past. They allow contracts as few as four days into the future, so I imagine they incorporate current weather forecasts. And the FAQ implies that some form of market feedback occurs, raising prices on contract terms that are in high demand.
Interface is important. WeatherBill shows that a very complicated combinatorial market can be presented in a natural and intuitive way. Though greater expressiveness can mean greater complexity and confusion, Tuomas Sandholm is fond of pointing out that, when done right, expressiveness actually simplifies things by allowing users to speak in terms they are familiar with. WeatherBill — and to an extent Yoopick IMHO — are examples of this somewhat counterintuitive principle at work.
There is another quote from WeatherBill’s FAQ that alludes to an even higher degree of combinatorics coming soon:
Currently you can only price contracts based on one weather measurement. We’re working on making it possible to use more than one measurement, and hope to make it available soon.
If so, I can imagine the number of possible insurance contracts quickly growing into the billions or more with prices hinging on interdependencies among weather events.
Finally, back to the US government treating me like a child. It turns out that only a very limited set of people can buy contracts on WeatherBill, mainly businesses and multi-millionaires who aren’t speculators. In fact, the rules of who can play are a convoluted jumble that I believe are based on regulations from the US Commodity Futures Trading Commission.
Luckily, WeatherBill provides a nice “choose your own adventure” style navigation flow to determine whether you are allowed to participate. Most people will quickly find they are not eligible. (I don’t officially endorse the CYOA standard of re-starting over and over again until you pass.)
Even if red tape locks the average consumer out of direct access, clever companies are stepping in to mediate. In a nice intro piece on WeatherBill, Newsweek mentions that Priceline used WeatherBill to back a “Sunshine Guaranteed” promotion offering refunds to customers whose trips were rained out.
Can you think of other end-arounds to bring WeatherBill functionality to the masses? What other forms of expressive insurance would you like to see?
We just added a new feature to Yoopick designed especially for Frenchmen Chris and Emile and citizens of nineteen other countries to place their swagor* on how many Olympic medals they think their country will win.
We’ve argued that the Yoopick interface is useful for predicting almost any kind of number, and since medal count is indeed a number, we thought we’d give it a try.
I mostly side with Lukas and Panos on the fantastic potential of Amazon’s Mechanical Turk, a crowdsourcing service specializing in tiny payments for simple tasks that require human brainpower, like labeling images. Within the field of computer science alone, this type of service will revolutionize how empirical research is done in communities from CHI to SIGIR, powering unprecedented speed and scale at low cost (here are twoexamples). My guess is that the impact will be even larger in the social sciences; already, a number of folks in Yahoo’s Social Dynamics research group have started running studies on mturk. (A side question is how university review boards will react.)
However there is a seedier side to mturk, and I’m of two minds about it. Some people use the service to hire sockpuppets to enter bogus ratings and reviews about their products and engage in other forms of spam. (Actually this appears to violate mturk’s stated policies.)
For example, Samuel Deskin is offering up to ten cents to turkers willing to promote his new personalized start page samfind.
EARN TEN CENTS WITH THE BONUS – EASY MONEY – JUST VOTE FOR US AND COMMENT ABOUT US
EARN FOUR CENTS IF YOU:
1. Set up an anoymous email account likke gmail or yahoo so you can register on #2 anonymously
2. Visit http://thesearchrace.com/signup.php and sign up for an account – using your anonymous email account.
3. Visit http://www.thesearchrace.com/recent.php and vote for:
samfind
By clcking “Pick”
SIX CENTS BONUS:
4. Visit the COMMENTS Page on The Search Race, it is the Button Right Next to “Picks” on this page: http://www.thesearchrace.com/recent.php and
5. Say something awesome about samfind (http://samfind.com) on The Search Race’s Comments page.
Make sure to:
1. Tell us that you Picked us.
2. Copy and Paste the Comment you typed on The Search Race’s Comment page here so we know you wrote it and we will give you the bonus!
Another type of task on mturk involves taking a piece of text and paraphrasing it so that the words are different but the meaning remains the same. Here is an example:
Paraphrase This Paragraph
Here’s the original paragraph:
You’re probably wondering how to apply a wrinkle filler to your skin. The good news is that it’s easy! There are a number of different products on the market for anti aging skin care. Each one comes with its own special application instructions, which you should always make sure to read and carefully follow. In general, however, most anti aging skin care products are simply applied to the skin and left to soak in.
Requirements:
1. Use the same writing style as much as possible.
2. Vary at least 50% of the words and phrases – but keep the same concepts. Use obviously different sentences! Your paragraph should not be just a copy of the first with a few word replacements.
3. Any keywords listed in bold in the above paragraph must be included in your paraphrase.
4. The above paragraph contains 75 words… yours must contain at least 64 words and not more than 101 words.
5. Write using American English.
6. No obvious spelling or grammar mistakes. Please use a spell-checker before submitting. A free online spell checker can be found at www.spellcheck.net.
If you find it easier to paraphrase sentence-by-sentence, then do that. Please do not enter anything in the textbox other than your written paragraph. Thanks!
I have no direct evidence, but I imagine such a task is used to create splogs (I once found what seems like such a “paraphrasing splog”), ad traps, email spam, or other plagiarized content.
It’s possible that paid spam is hitting my blog (either that or I’m overly paranoid). I’m beginning to receive comments that are almost surely coming from humans, both because they clearly reference the content of the post and because they pass the re-captcha test. However, the author’s URL seems to point to an ad trap. I wonder if these commenters (who are particularly hard to catch — you have to bother to click on the author URL) are paid workers of some crowdsourcing service?
Can and should Amazon try to filter away these kinds dubious uses of Mechanical Turk? Or is it better to have this inevitable form of economic activity out in the open? One could argue that at least systems like mturk impose a tax on pollution and spam, something long argued as an economic force to reduce spam.
My main objection to these activities is the lack of disclosure. Advertisements and press releases are paid for, but everyone knows it, and usually the funding source is known. However, the ratings, reviews, and paraphrased text coming out of mturk masquerade as authentic opinions and original content. I absolutely want mturk to succeed — it’s an innovative service of tremendous value, one of many to come out of Amazon recently — but I believe Amazon is risking a minor PR backlash by allowing these activities to flow through its servers and by profiting from them.
A collection of (relatively) recent yellow bricks on the road to widespread use of prediction markets:
Wired Magazine features an article on political prediction markets infused with a mostly healthy if occasionally misguided skepticism. I was struck most by the nonchalant subtext that prediction markets have gone mainstream: “As you’ve no doubt heard…”
Two nice articles at MSNBC and Business Week describe the context and opportunity presented by the CFTC’s mayday asking for guidance on regulating prediction markets in the US.
In May, twenty-two economists, including two with Nobel Prize credentials (expect that number to grow), published a position paper in Science calling on the US government to legalize and regulate socially valuable prediction markets.
Mr. Murphy may be hard at work orchestrating one of his signature ironies. Picture this: Prediction market proponents (including me) aren’t careful and get what they wish for: The CFTC takes prediction markets under its regulatory purview. Then, efforts to legalize Internet gambling in the US succeed, opening up an enormous and fabulously lucrative business that the “socially good” prediction market operators are legislated out of, mired instead in a separate regulatory goop of their own making.
Sorry folks, I just released 26 comments from purgatory where they had been sitting for as long as 58 days. All pending comments have now been approved and posted. I’ll try to go through them soon and respond where appropriate.
About two months ago I changed my WordPress configuration and it turns out that comments were piling up for moderation without email notification, and I failed to spot the growing queue until now.
Since I’m using re-captcha and have turned off trackbacks, I shouldn’t need to moderate comments going forward, so I’ve turned off moderation (fingers crossed).
I’m happy to announce the public beta launch of Yoopick, a sports prediction contest with a twist.
You pick any range you think the score difference or point spread of the game will fall into, for example you might pick Pittsburgh wins by between 2 and 11 points.
The more your prediction is viewed as unlikely by others, and the more you’re willing to stake on your prediction, the more you stand to gain. Of course it’s all for fun: you win and lose bragging rights only.
You can play with and against your friends on Facebook.
You can settle a pick even before the game is over, much like selling a stock in the stock market. Depending on what other players have done in the interim, you may be left with a gain or loss. You gain if you were one of the first to pick a popular outcome.
If you run out of credit, you can “work off your debt” by helping to digitize old books via the recaptcha project.
Those are the highlights if you want to go play the game. If you’re interested in more details, read on…
Motivation, Design, and Research Goals
There are a great many sources of sports predictions, including expertcommunities, statistical number crunchers, bookmakers, and bettingexchanges. Many of these sources are highly accurate, however they typically focus on predicting the outright or spread-adjusted winner of the game. Our goal is to obtain more information about the final score, including the relative likelihood of each point spread. For example, if our system is working, on average there should be more weight put on point spreads of 3 and 7 in NFL games than on 2,4,6, or 8.
We chose sports as a test domain to tap into the avid fan base and the armies of arm chair (and Aeron chair) prognosticators out there. However, the same approach should translate well to any situation where you’d like to predict a number, for example, the vote share of a politician or the volume of sales of your company’s widget. In addition to giving you the expected value of the number, our approach gives you the confidence or variance of the prediction — in fact, it gives you the entire probability distribution, or the likelihood of every possible value of the number.
Underneath the hood, Yoopick is a type of combinatorial prediction market where the possible outcomes are the values of the point spread, and each pick is a purchase of a bundle of outcomes in a given interval. We use Hanson’s logarithmic market scoring rules market maker to price the picks — that is, to set the risk/reward ratio. This pricing mechanism also determines the gain or loss when picks are settled early.
Wins and losses on Yoopick are measured in milliyootles, a social currency useful for expressing thanks.
Our market maker can — and we expect will — lose yootles on average. Stated another way, we expect players as a whole to gain on average. At the same time, we actively work to improve our market maker to limit its losses to control inflation in the game.
Because the outcomes of a game are tied together in a unified market, picks in one region automatically affect the price of picks in other regions in a logically consistent way. Players have considerable flexibility in how and what information they can inject into the market. In particular, players can replicate the standard picks like outright winner and spread-adjusted winner if they want, or they can go beyond to pick any interval of the point spread. No matter the form of the pick, all the information flows into a single market that aggregates everything in a unified prediction. In contrast, at venues from Wall Street to Churchill Downs to High Street to Las Vegas Boulevard, markets with many outcomes are usually split into independent one-dimensional markets.
Our goal is to test whether our market design is indeed able to elicit more information than traditional methods. We hope you have fun playing in our Petri dish.
Sharad Goel
David Pennock
Daniel Reeves
Prasenjit Sarkar
Cong Yu
Musings of a computer scientist on predictions, odds, and markets
