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A Website and Weblog about Topics and Issues discussed in the book
Smart Mobs: The Next Social Revolution by Howard Rheingold

Can the wisdom of crowds improve stock trading? Piqqem thinks so.
February 18th, 2009

The recently launched service Piqqem is premised on the idea that, collectively, we all know more about companies and the potential value of their stocks than do we individually — even than seasoned traders. From the FAQ:

Piqqem differs from other sites in that we believe the crowd has more knowledge than any single individual. Instead of looking for the best individual stock picker and weighting votes based on investment ability, we look at aggregate opinion and allow everyone to vote as much as they want. This orientation towards crowd wisdom manifests itself in our crowd indicators, such as top rated stocks, most active stocks, stocks with most rising sentiment, and stocks with most falling sentiment.

In theory, the aggregate data generated through Piqqem will enable its users to make better decisions about which stocks to buy and sell, by allowing users to vote on individual companies in order to make predictions. Most recently, Piqqem alerted SmartMobs to their new integration with Twitter, as a potentially powerful tool for analyzing and influencing the stock market.

The stock market is, of course, itself already a product of collective thought, if unpredictably so. It will be interesting to see whether non-expert users take up a service like Piqqem, or if its users remain those already knowledgeable about equities and the world of finance.

Piqqem: A Potential Smart Mob of Investors
October 22nd, 2008

As readers of this blog well know, the wisdom of crowds manifests itself when the aggregated thinking of a crowd is more accurate than that of even an expert individual. This blog has seen numerous examples of leveraging crowd wisdom, such as a crowd-curated exhibit at the Brooklyn Museum and a crowdsourced restaurant ingredients in Washington. But even though the wisdom of crowds has manifested itself from economics to psychology, we tend to go about our stock investing based on the wisdom of few individuals – such as large institutional investors, financial analysts, company CEOs. So why not apply the wisdom of crowds to stock market predictions?

Enter Piqqem, a new web app which does precisely that. Piqqem captures predictions of stock movements from its users, and displays the results in a variety of interesting and valuable ways. Put simply, Piqqem captures and displays the stock market wisdom of crowds. Even if the crowd turns out to be not-so-wise, its predictions are still useful if they’re consistent, because you can always choose to bet with or against the crowd. And even if the crowd’s predictions turn out to be inconsistent, capturing them is still worthwhile in that it explores whether the crowd can predict stock movements more successfully than the seasoned individual – a fascinating and open question, especially at a time when stock markets are turbulent and crowd sentiments can add valuable insight beyond traditional stock market analysis. Ultimately, crowd predictions are intended as one in a portfolio of sources on stock information; and a powerful source in that it represents a distribution of predictions versus a single, albeit expert, one.

Every day, the biggest investors use expert opinions to move the market. Piqqem enables users to aggregate their opinions and potentially move the market together. It is therefore a technology enabling the emergence of crowd wisdom, and – if acted upon – of smart mobs of investors.

Can the crowd predict the movement of stocks more successfully than even the seasoned individual? Can Piqqem enable a smart mob of investors? Join the Piqqem crowd to find out…

Crowdsourcing vs. Wisdom of Crowds
March 8th, 2009

“Crowdsourcing” and “the wisdom of crowds”: We hear these two terms with increasing frequency, and throw them around quite a bit here at Smart Mobs. But there’s a meaningful difference between them, so for purposes of clarity, I thought I’d dedicate a blog post to it. (And of course I’ll be using what could be considered the crowned jewel of crowdsourcing to do so: Wikipedia.)

According to Wikipedians, crowdsourcing is “the act of taking a task traditionally performed by an employee or contractor, and outsourcing it to an undefined, generally large group of people, in the form of an open call.” Basically, you’re taking a task and outsourcing it to a crowd; hence crowdsourcing. Examples include Google’s Image Labeler, which takes the task of labeling images, and outsources it to anyone who wants to play a simple game, and Threadless T’s, which outsources the task of designing t-shirts to its users by letting them submit designs and vote on them (shameless plug for my submissions here). Amazon even hosts a marketplace specifically dedicated to crowdsourcing simple tasks which computers are unable to do, called the Mechanical Turk, which has been used for applications ranging from searching satellite images for evidence of missing aviator Steve Fosset, to artist Aaron Koblin’s The Sheep Market, a collection of 10,000 sheep made by workers paid 2 cents to “draw a sheep facing to the left.”

The wisdom of crowds, on the other hand, is known to Wikipedians as James Surowiecki’s book by the same name, defined as a phenomenon where “the aggregation of information in groups, [results] in decisions that…are often better than could have been made by any single member of the group.” The quintessential example is that of guessing how many jelly beans are in a jar, where averaging the guesses of many people is more accurate than the guess of one expert individual, and the wisdom of crowds also manifests itself from sports betting to traditional opinion polls.

Applications that leverage the wisdom of crowds are necessarily crowdsourced, because they outsource the task of voting, predicting, guessing, or otherwise submitting an opinion to a crowd. On the flipside, crowdsourcing apps do not necessarily leverage the wisdom of crowds; Koblin’s Sheep Market workers weren’t voting on what a sheep facing left should look like, but were merely submitting their own drawings.

Wikipedia is a crowdsourcing app in that it outsources the task of creating an encyclopedia to a large distributed population. There’s been considerable debate about whether Wikipedia leverages crowd wisdom, but I’d argue that it doesn’t because – at least in Surowiecki’s conception of it – the wisdom of crowds is only applicable to quantifiable, objective data.

Piqqem, an app that essentially gauges the stock market wisdom of the crowd (and that has already been written about here on Smart Mobs) is both a crowdsourcing app and a wisdom of crowds app, in that it outsources the task of stock market predicting to a crowd, and aggregates the crowd’s opinion on quantifiable and objective data, namely the movement of stocks. So I guess you could say that Piqqem crowdsources the stock market wisdom of crowds. (If that last sentence makes zero sense, you can indeed make sense of it!)

And finally, the original raison d’etre of this blog. How does the concept of smart mobs interface with those of crowdsourcing and the wisdom of crowds? Broadly defined, smart mobs are instances of technology-enabled collectively intelligent behavior. They therefore imply more agency and intention on behalf of their participants than crowdsourcing would suggest, hinting that the two may be incompatible. Meanwhile, smart mobs that produce quantifiably and objectively accurate decisions could be said to exhibit the wisdom of crowds, hence the name for my previous Smart Mobs post about Piqqem, namely, Piqqem: a smart mob of investors?. This suggests that smart mobs may or may not exhibit the wisdom of crowds; wisecrowds are a type of smart mob because the former is hierarchically lower – ontologically speaking – than the latter. Still, I consider the relationship between the concept of smart mobs and those of crowdsourcing and the wisdom of crowds to remain somewhat of an open question. Dear wise crowd of Smart Mobs: what do you think?




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