We believe that we can harness the wisdom of crowds to predict a whole range of future outcomes on Ranker.
Los Angeles, CA (PRWEB) May 13, 2013
At the end of each year, there are usually media stories that compile lists of famous people who have passed away. These lists usually cause us to pause and reflect. Lists like Celebrity Death Pool 2013 on Ranker, however, give us an opportunity to make (macabre) predictions about recent celebrity deaths. Can the wisdom of crowds predict recent celebrity deaths?
An analysis of recent celebrity deaths by UCI professor of cognitive sciences, Michael Lee, using recently published algorithms revealed that the aggregated opinions of Ranker users about recent celebrity deaths were relatively accurate. Aggregated predictions were better than chance and better than all but one individual users' opinion.
Lee was interested in whether “wisdom of the crowd” methods could be applied to aggregate the individual predictions. Ranker data involved the lists provided by a total of 27 users up until early in 2013. Some users predicted as many as 25 deaths, while some made a single prediction. The median number of predictions was eight, and, in total, 99 celebrities were included in at least one list. At the time of analysis, six of the 99 celebrities had passed away.
The net result of Lee's modeling was a list of all 99 celebrities, in an order that combines the rankings provided by everybody, using algorithms developed by his research team. The top 5 in this aggregated list, for the morbidly curious, were Hugo Chavez (already a correct prediction), Fidel Castro, Zsa Zsa Gabor, Abe Vigoda, and Kirk Douglas. Aggregate wisdom can be assessed by working down the list, and keeping track of correct predictions. This assessment is shown by the green line in the graph. Because the list includes all 99 celebrities, it will always find the six who have already recently passed away, and the names of those celebrities are shown at the top, in the place they occur in the aggregated list.
The interesting part in assessing the wisdom of the Ranker crowd is how early in the list it makes correct predictions about recent celebrity deaths. Thus, the more quickly the green line goes up as it moves to the right, the better the predictions of the crowd. From the graph, we can see that the crowd is currently performing quite well, and is certainly about the “chance” line, represented by the dotted diagonal. (This line corresponds to the average performance of a randomly-ordered list).
We can also see that the crowd is performing as well as, or better than, all but one of the individual users. Their blue circles are shown again along with crowd performance. Circles that lie above and to the left of the green line indicate users outperforming the crowd, and there is only one of these. Interestingly, predicting celebrity deaths by using age, and starting with the oldest celebrity first, does not perform well. This seemingly sensible heuristic is assessed by the red line, but is outperformed by the crowd and many users.
"Successfully aggregating opinions is a cornerstone of prediction markets like the New York Stock Exchange, InTrade, and the Hollywood Stock Exchange," explained Ravi Iyer, Ranker's Principal Data Scientist. "We don't plan on focusing on such macabre topics, but our preliminary success in predicting box office receipts and celebrity deaths leads us to believe that we can harness the wisdom of crowds to predict a whole range of future outcomes on our platform."