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I APPRECIATE JED CHRISTIANSEN'S SUMMARY of my paper with Eric Zitzewitz and Justin Wolfers. Go check it out. To me, the most interesting line is the following: The second half of the paper examined the transmission of information within Google based on the authors’ analysis of the traders and their behaviours. While there is some really interesting analysis there, it has more to do with organisational behaviour than being directly applicable to prediction markets[.] This is not the first reaction along these lines. I am perplexed by the response. I can understand why other companies may not want to replicate our analysis of information flows. Perhaps it wouldn't be worth the effort. Perhaps they would get identical results. And perhaps the company wouldn't have the all the necessary data.
However, I expected that people could easily see value in the analysis of granular trade-by-trade data -- especially if that data is joined with data about traders and outside events happening at the moment of the trades. We described one very generic application of this approach, but you can imagine much more actionable and company-specific ones.
I will mention one: The data contains real-time metrics on the distribution of knowledge and attitudes within a firm at a highly granular level. You can get metrics on for specific of the firm, for specific classes of employees and for specific topics. You can do this for either customers or employees, and have the metrics for any moment in time. The quality of these metrics will be extremely strong, because participants have been incentivized to reveal their true expectations.
Our analysis spoke in very general terms about the flow of information between Google employees -- we don't reference specific groups or draw distinctions between them -- which is where a lot of actionable data was. Trade-by-trade data can reveal characteristics of specific working groups: What they know, how they feel, how they process and share information and how all of that changes over time.
I didn't try to put any of this in the paper because the conclusions would be sensitive, and I thought this application was pretty obvious to anybody who understood our methodology.
UPDATE: Our findings about the clustering of attitudes should also inform anyone who thinks that diversity is important for crowd-wisdom applications -- as James Surowiecki famously suggests in The Wisdom of Crowds.
Our analysis suggests that groupthink primarily happens within language networks and small physical spaces (with social/professional networks playing a secondary role, and demographic networks playing a non-existent one). Remember that as you're selecting your traders. If they already work/sit/chat together, the groupthink may already exist and the market won't cure it.
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Disclaimer: Opinions expressed on this site are the author's and not necessarily his employer's.
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