August 20, 2010, Sunnyvale, CA

The last decade has witnessed the emergence of enormous scale artifacts resulting from the independent action of hundreds of millions of people; for example, web repositories, social networks, mobile communication patterns, and consumption in “limitless” stores… the first Research and Analysis of Tail phenomena Symposium (RATS)… will explore the different computational, statistical, and modeling problems related to tail phenomena… We are particularly encouraging summer interns in any of the Bay Area research centers to join us in the event.
We will start with a video welcome by Chris Anderson (Wired), followed by a series of invited talks by Michael Mitzenmacher (Harvard), Aaron Clauset (Univ. of Colorado), Neel Sundaresan (eBay), Sharad Goel (Yahoo! Research, NY) and Michael Schwarz (Yahoo! Research, CA).

We invite proposals for short (20 minute) talks from students and researchers working in the area.

CrowdCof2010: 1st Annual Conference on the Future of Distributed Work

October 4, 2010, San Francisco, CA

Were you crowdsourcing before it was cool? We want to hear about your projects.

We are inviting submissions on all topics regarding crowdsourcing, including:

• Past, present, and future of crowdsourcing
• Quality assurance and metrics
• Social and economic implications of crowdsourcing
• Task design/Worker incentives
• Innovative projects, experiments, and applications
• Submission Guidelines

Deadline: Sept. 1

CrowdConf will bring together researchers, technologists, outsourcing entrepreneurs, legal scholars, and artists for the first time to discuss how crowdsourcing is transforming human computation and the future of work.

Confirmed Speakers:
Sharon Chirella: Vice President, Amazon Mechanical Turk
Tim Ferriss : Author, The 4-Hour Work Week
David Alan Grier: Author, When Computers Were Human
Barney Pell: Partner, Search Strategist, and Evangelist, Microsoft
Maynard Webb: CEO, LiveOps
Jonathan Zittrain: Professor of Law and Computer Science, Harvard

Computational Social Science and the Wisdom of Crowds Workshop at NIPS 2010

December 10th or 11th, 2010, Whistler, Canada

We welcome contributions on theoretical models, empirical work, and everything in between, including but not limited to:

• Automatic aggregation of opinions or knowledge
• Prediction markets / information markets
• Incentives in social computation (e.g., games with a purpose)
• Studies of events and trends (e.g., in politics)
• Analysis of and experiments on distributed collaboration and consensus-building, including crowdsourcing (e.g., Mechanical Turk) and peer-production systems (e.g., Wikipedia and Yahoo! Answers)
• Group dynamics and decision-making
• Modeling network interaction content (e.g., text analysis of blog posts, tweets, emails, chats, etc.)
• Social networks

[Covers] computational social science… [and] social computing… with an emphasis on the role of
machine learning…

Deadline for submissions: Friday October 8, 2010

More people are playing Predictalot today than Mafia Wars or Zynga Poker… On Yahoo!, that is.

In fact, Predictalot is the #1 game app on Yahoo! Apps by daily count. By monthly count, we are 5th and rising.

A prediction is being made about every three minutes.

Come join the fun.

Yahoo! Lab’s own Predictalot market is now live and waiting for you to place almost any prediction your heart desires about the World Cup in South Africa.

Here are some terribly useful things you can learn this time around. All numbers are subject to change, and that’s kind of the point:

• There’s a 37% chance Brazil and Spain will both make it to the final game; there’s only a 15% chance that neither of them will make it
• There’s is a 1 in 25 chance Portugal will win the cup; 1 in 50 for Argentina
• 42.92% chance that a country that has never won before will win
• 19.07% chance that Australia will advance further than England
• 65.71% chance that Denmark, Italy, Mexico and United States all will not advance to Semifinals
• Follow Predictalot on twitter for more

If you think these odds are wrong, place your virtual wager and earn some intangible bragging rights. You can sell your prediction any time for points, even in the middle of a match, just like the stock market.

There are millions of predictions available, yet I really believe ours is the simplest prediction market interface to date. (Do you disagree, Leslie?) We have an excellent conversion rate, or percent of people who visit the site who go on to place at least one prediction — for March Madness, that rate was about 1 in 5. One of our main goals was to hide the underlying complexity and make the app fast, easy, and fun to use. I personally am thrilled with the result, but please go judge for yourself and tell us what you think.

In the first version of Predictalot, people went well beyond picking the obvious like who will win. For example, they created almost 4,000 “three-dimensional” predictions that compared one team against two others, like “Butler will advance further than Kentucky and Purdue”.

If you’re not sure what to predict, you can now check out the streaming updates of what other people are predicting in your social circle and around the world:

Also new this time, you can join a group and challenge your friends. You can track how you stack up in each of your groups and across the globe. We now provide live match updates right within the app for your convenience.

If you have the Yahoo! Toolbar (if not, try the World Cup toolbar), you can play Predictalot directly from the toolbar without leaving the webpage you’re on, even if it’s Google.

Bringing Predictalot to life has been a truly interdisciplinary effort. On our team we have computer scientists and economists to work out the market math, and engineers to turn those equations into something real that is fast and easy to use. Predictalot is built on the Yahoo! Application Platform, an invaluable service (open to any developer) that makes it easy to make engaging and social apps for a huge audience with built-in distribution. And we owe a great deal to promotion from well-established Yahoo! properties like Fantasy Sports and Games.

We’re excited about this second iteration of Predictalot and hope you join us as the matches continue in South Africa. We invite everyone to join, though please do keep in mind that the game is in beta, or experimental, mode. (If you prefer a more polished experience, check out the official Yahoo! Fantasy Sports World Soccer game.) We hope it’s both fun to play and helps us learn something scientifically interesting.

Read more here, here, and here.

Or watch a screencast of how to play:

On April 5th, we will know who is champion. In the meantime, it’s anybody’s guess: any of 9.2 quintillion things could in principle happen.

At Predictalot it’s your guess. Make almost any prediction you can think of, like Duke will win go further than both Kansas and Kentucky, or the Atlantic Coast will lose more games than the Big East. There’s even the alphabet challenge: you pick six letters that include among them the first letters of all four final-four teams.

Following Selection Sunday yesterday, the full range of prediction types are now enabled in Predictalot encompassing hundreds of millions of predictions about your favorite teams, conferences, and regions. Check it out. Place a prediction or just lurk to see whether the crowd thinks St. Mary’s is this year’s Cinderella.

Come join our mad science experiment where crowd wisdom meets basketball madness. We’ve had many ups and down already — for example sampling is way trickier than I naively assumed initially — and I’m sure there is more to come, but that’s part of what makes building things based on unsolved scientific questions fun. Read more about the technical details in my previous posts and on the Yahoo! Research website.

And for the best general-audience description of the game, see the Yahoo! corporate blog.

Update: Read about us on the New York Times and VentureBeat.

You can even get your fix on Safari on iPhone!

Below is a graph of our exponential user growth over the last couple days. Come join the stampede!

The basic game play is simple: select a prediction type, customize it, and invest points on it. Yet you’ll never run out of odds to explore: there are hundreds of millions of predictions you can make. The odds on each update continuously based on other players’ predictions and the on-court action.

Predictalot is a Yahoo! App, so you can play it at apps.yahoo.com or you can add it to your Yahoo! home page. I have to admit, it’s an incredible feeling to play a game I helped design right on the Yahoo! home page.

That’s all you need to get started. If you’re curious and would like a peek under the hood, read on: there’s some interesting technology hidden in the engine.

Background and Details

Predictalot is a true combinatorial prediction market of the sort academics like us and Robin Hanson have been dreaming about since early in the decade. We built the first version during an internal Yahoo! Hack Day. Finally, we leveraged the Yahoo! Application Platform to quickly build a public version of the game. (Note that anyone can develop a YAP app that’s visible to millions — there’s good sample code, it supports YUI and OpenSocial, and it’s easy to get started.) After many fits and starts, late nights, and eventually all nights, we’re proud and excited to go live with Predictalot version 1.0. I can’t rave enough about the talent and dedication of the research engineers who gave the game a professional look and feel and production speed, turning a pie-in-the-sky idea into reality. We have many features and upgrades in mind for future versions, but the core functionality is in place and we hope you enjoy the game.

In the tournament, after the play-in game, the 64 top college basketball teams play 63 games in a single elimination tournament. So there are 2 to the power 63 or 9.2 quintillion total possible outcomes, or ways the entire tournament can unfold. Predictalot implicitly keeps track of the odds for them all. To put this in perspective, it’s estimated that there are about 10 quintillion individual insects on Earth. Of course, for all practical purposes, we can’t store 9.2 quintillion numbers, even with today’s computers. Instead, we compute the odds for any outcome on the fly by scanning through the predictions placed so far.

A prediction is a statement, like Duke will win in the first round, that will be either true or false in the final outcome. In this case, the prediction is true in exactly half, or 2 to the power 62 outcomes. (Note this does not mean the odds are 50% — remember the outcomes themselves are not all equally likely.) In theory, Predictalot can support predictions on any set of outcomes. That’s 2 to the power 2 to the power 63, or more than a googol predictions. For now, we restrict you to “only” hundreds of millions of predictions categorized into thirteen types. Computing the odds of a prediction precisely is too slow. Technically, the problem is #P-hard: as hard as counting SAT and harder than the travelling salesman problem. So we must resort to approximating the odds by randomly sampling the outcome space. Sampling is a tricky business — equal parts art and science — and we’re still actively exploring ways to increase the speed, stability, and accuracy of our sampling.

Because we track all possible outcomes, the predictions are automatically interconnected in ways you would expect. A large play on Duke to win the tournament instantly and automatically increases the odds of Duke winning in the first round; after all, Duke can’t win the whole thing without getting past the first round.

With 9.2 quintillion outcomes, Predictalot is to our knowledge the largest prediction market built, testing the limits of what the wisdom of crowds can produce. Predictalot is a game, and we hope it’s fun to play. We’d also like to pave the way for serious use of combinatorial prediction market technology.

Why did Yahoo! build this? Predictalot is a smarter market, letting humans and computers each do what they do best. People enter predictions in simple terms they understand like how one team fares against another. The computer handles the massive yet methodical number crunching needed to combine all the pieces together into a coherent overall prediction of a complex event. Markets like Predictalot, WeatherBill, CombineNet, and Internet advertising systems, to name a few, represent the evolution of markets in the digital age, empowering users with extreme customization. More and more, matching buyers with sellers — the core function of markets — requires sophisticated algorithms, including machine learning and optimization. Predictalot attempts to illustrate this trend in an entertaining way.

David Pennock
Mani Abrol, Janet George, Tom Gulik, Mridul Muralidharan, Sudar Muthu, Navneet Nair, Abe Othman, Daniel Reeves, Pras Sarkar

First off, I cheated. I went to sleep in a hotel room rather than hack all through the night. (Even in college I woke up at 4am rather than pull an all nighter.) Still, I made decent progress on some pet projects including combinatorial betting. Daniel, Sharad, and Winter from Yahoo! Research New York participated for real, working through the night. Returning in the morning showered and caffeinated to greet the sleepwalkers was a little surreal. A number of ex-Yahoos joined the festivities including David Yang, Mor Naaman, and Chad Dickerson. (Havi joked that Yahoo! is like finishing school for entrepreneurs. If you count Yahoo! capture and releases like Mark Cuban and Paul Graham, the spreading influence is enormous.)

Clay Shirky kicked off the event. He’s a fantastic speaker — watch his talk here. His punch line — that successful communities like facebook, twitter, flickr, and wikipedia start small and cohesive (as opposed to large and fragmented: see Yahoo! 360) — was aimed perfectly at the many founders and foundreamers in the audience. There were speakers from Mint and foursquare and tutorials on the Yahoo! Application Platform, Yahoo! Query Language (the most popular service), Yahoo! TV widgets, and more. There was a round of Ignite NYC, a barrage of twenty-slides-in-five-minutes talks, some educational (geek’s guide to patents), some charitable (aid to South America), some hilarious (spaceman from outerspace), some thought provoking (makerbot 3d printers), and many all of the above (meta mechanical turk; the Emoji translation of Moby Dick). Watch the Ignite talks here.

A bunch of small touches made the event memorable, including a steampunk-themed hacking hall complete with retroRed Victorian couches, portraits of hackers through history, funky tweet-streaming sculptures, chalk drawings of old patents, power cords dangling from hanging bird cages, and a guitarhero-foosball corner. The food was tasty and at times eccentric, like the hot dog stand and toppings bar under a rainbow umbrella, ice cream cart, and old-fashioned popcorn machine. There was plenty of beer, coffee, red bull, sliders, and cookies, and even (gasp) vegan fare, salmon, and salad.

I give the event an A for style (decor, food) and content (talks, hacks, organization). The one sour note was the wireless — certainly a key ingredient for a good hack day — which began flaky and ended slow but acceptable.

I attended the YAP tutorial and created a rudimentary application. I was pleasantly surprised how simple the process was — the documentation and sample code are great. You can get the hello world app (complete with social hooks) running and add some ajax magic within minutes.

By far one of the coolest sights was the MakerBot Industries 3D printer in action. It sucks in plastic wire, melts it, and deposits it in perfect formation to produce coins, busts, parts for itself, or almost anything in the thingiverse. For Hack Day, the device printed news headlines in peanut butter on toast. We met an nyc resistor who was working on a conveyer belt mechanism for his own MakerBot printer, and he invited us to craft night at their shared hackspace in Brooklyn (a place that would be heaven for my dad and brother; Sharad, Jake, Daniel, and Bethany went to check it out).

I missed the tutorial on Yahoo! TV widgets but I’d like to learn more. They are now in most major TV brands including Sony, Samsung, and LG — millions of sets around the world in the coming months. (The Sony won editor’s choice in the Sept 2009 issue of Wired magazine; the Samsung and LG rated close behind. The sole TV reviewed without Yahoo! Widgets, a Panasonic, was ridiculed for is clunky Viera Cast online interface.) If you’re an internet video startup, like my friend, you need a widget channel. Personally, I’d love to see a sports game tracker that highlights pivotal moments by monitoring in-game betting odds.

Footnote: Two Yahoos made a humorous video (that’s both self-promotional and -deprecating) on what people in Times Square think ‘hacker’ means:

See Paul Tarjan and Christian Heilmann for real definitions.

The 24-Hour Hackathon begins Friday afternoon. We encourage you to play around with Yahoo!’s Open Platforms and APIs like YAP, YQL, YUI, TVWidgets, our Social APIs, and more. And of course, feel free to use other APIs, developer tools and whatever software/hardware floats your boat…

At the end of the 24 hours, the hackers will have the chance to debut their hack and winners will be awarded with some enviable prizes…

And of course we will keep you well fed and hydrated throughout the two days. There will also be sleeping areas in case you want to take a nap.

Previous: the what and why of Open Hack.

I told the audience that they could learn more by searching for “cftc yahoo google” in their favorite search engine, showing the Yahoo! Search results with MidasOracle’s coverage at the top.²

It turns out that was poor advice. 63.7% of the audience probably won’t find what they’re looking for using that search.³

If some search engines don’t surface the MidasOracle post, I’m hoping they’ll find this.

And back to the effort to guide the CFTC: I hope other people and companies will join. The CFTC’s request for help itself displays a clear understanding of the science and practice of prediction markets and a real willingness to listen. The more organizations that speak out in support, the greater chance we have of convincing the CFTC to take action and open the door to innovation and experimentation.

And there’s no doubt that digital representations of social ties add value. Facebook does improve people’s lives.¹

The puzzle, and one of the key challenges facing companies like Facebook, Google, and Yahoo!., is how social media can make money. So far the evidence is most users won’t pay directly, which leaves ideas like virtual goods, community marketplaces, app stores, and, of course, advertising. Unfortunately, although we know great ways to advertise to people searching, and decent ways to advertise to people viewing content, it’s less clear how to advertise to people communicating.

P&G’s Ted McConnell puts it bluntly:

What in heaven’s name made you think you could monetize the real estate in which somebody is breaking up with their girlfriend?

Riffing off of this quote, Wired asks the $15 billion question: Is social advertising an oxymoron?:

So, what if social media and advertising just don’t mix?

SocialMedia.com, a social advertising startup, begs to differ (hat tip to Cong Yu), reacting to the same provocative McConnell quote. Their answer:

Advertisers only pay when users volunteer to say something about the brand to their friends.

Indeed, this sort of paid version of Bem+Wom (“BEtter Mousetrap + Word Of Mouth”) — more on this in the next post — is one of the first things people think of when pondering how to monetize a social network. But can it work well and if so, how?

It’s a great resource for students to learn about the area and find meaty research problems. There’s also a chance for graduate students to earn $5000 in seed funding, work with Yahoo! Research scientists and data, and attend a summit of like-minded students and scientists.

The challenges cover search, machine learning, data management, information extraction, economics, social science, statistics, multimedia, and computational advertising.

Here’s the list of challenges from the algorithmic economics group, my group. We hope it provides a clear picture of the goals of our group and the areas where progress is most needed.

We look forward to supporting students who love a challenge and would like to join us in building the next-generation Internet.