Of course, it's not that big data itself was to blame, just the interpretation of it. Nate, not sure what to tell you but that was a significant miss in this election, going all the way back into the primaries.
Of course, it's not that big data itself was to blame, just the interpretation of it. Nate, not sure what to tell you but that was a significant miss in this election, going all the way back into the primaries.
Even ignoring the model they basically called out this exact possibility at least twice in very recent articles. One saying that people where underestimating the likelihood of Trump winning the electoral college, despite losing the popular vote. And another pointing out that Trumps was within one standard polling error of winning the presidency and people where shouldn't ignore error margins on the published polls.
"To be honest, I’m kind of confused as to why people think it’s heretical for our model to give Trump a 1-in-3 chance — which does make him a fairly significant underdog, after all. There are a lot of ways to build models, and there are lots of factors that a model based on public polling, like ours, doesn’t consider.3 But the public polls — specifically including the highest-quality public polls — show a tight race in which turnout and late-deciding voters will determine the difference between a clear Clinton win, a narrow Clinton win and Trump finding his way to 270 electoral votes."
-- Nate Silvers on Nov 6
http://fivethirtyeight.com/features/election-update-dont-ign...
A better measure of closeness might be how many votes would have to change to change the winner. I think by that measure this election is incredibly tight.
Of course, nothing is likely to come close to 2000, where changing a mere 269 votes would have changed the outcome.
Maybe the result of maligning (and I'm using the term loosely here) the opposition voters results in statistically significant polling errors (echos of Brexit). Maybe word clouds can be used to suggest a lean toward one side of the error? An embarrassment index of sorts? I dunno.
Obviously not really a win for Silver, but I'll give him credit for being more conservative in his estimates than other models. You work with the data you have.
I mean the public perception of data, analytics, pollsters, etc. is now being discussed in the press as something that blatantly misses the "human" element.