I remember that interactive story. It was not what you describe. It was showing Hillary's chances of winning throughout the evening - she started at 90% or so, based on the polling averages they'd been running on a regular basis throughout the entire election season. Then, as the evening wore on, and results were not as the polling would indicate, her chances of winning dropped, dropped, and then obviously went to zero.
Now, I won't argue that in hindsight that was a pretty bad feature to run. I think it vastly overestimated reader ability to understand statistical probabilities, as well as the accuracy of polling data (the Brexit vote ought to have been an indicator to be cautious). But it absolutely wasn't showing false data that indicated Hillary was winning when she was not.
Everyone was wondering (both pro-trump and anti-trump) where the "90%" came from. Because it was pretty clear the race was not that obvious. People keep saying nobody saw it coming, but that's their emotion speaking. People just didn't want Donald Trump to win because they thought he's a joke, but objectively speaking people knew clearly that there were tons of his supporters around the U.S., and it was definitely NOT 90% chance that Hillary would win.
To me, THAT's the ultimate "fake news". Slapping a percentage number on it and putting it on the front page is just not right, especially when it's based on very subjective (and eventually false) speculative data.
"The front page had this interactive realtime story of how Hillary is supposedly winning"
I said:
"it absolutely wasn't showing false data that indicated Hillary was winning when she was not"
They're pretty clearly contradictory. That data, at no point, showed Hillary "supposedly" anything. You're making my point about readers not understanding statistical probabilities. 90% doesn't mean she's winning. It means she's got a 90% chance of winning, and there is a 10% chance she will lose. She lost.
> People keep saying nobody saw it coming, but that's their emotion speaking.
Quite the opposite. The data (that same data you're saying came from nowhere) showed that Hillary had a 90% chance of winning. There was variance in the polls, but pretty much all of them showed Hillary with an edge. Yes, there were a great many reports of people saying that there was a lot of Trump support across the country, but those reports are the very opposite of "objective" - they were thinly spread and anecdotal. Pretty much every newspaper ran stories interviewing those Trump supporters, but there was no hard data to quantify it.
Polling data isn't "subjective" and "speculative". There is a clearly defined methodology behind it. That methodology was incorrect in the 2016 election, and didn't accurate gauge support for two unprecedentedly unpopular candidates. That makes it "incorrect news", not "fake news".
You could argue that the news industry has relied too heavily on this sort of statistical prediction stuff, and I'd agree with you. But in 2012 FiveThirtyEight correctly predicted all but one state, and everyone absolutely lauded Nate Silver for it ("Is Nate Silver a witch?"). But really, what that meant is that each of Nate's predictions were the right side of 50%. And in 2016 they most definitely weren't.
Really, I think most of the incorrect predictions came from one error: assuming a higher level of independence between state results than is actually the case. Nate Silver/538 talk about this some, and they gave Trump the highest (~30%) chance of winning on election day.
All of these things could have occurred, but something definitely was wrong with the polling data. Nate Silver just like NYT gave Hillary a 90% chance at the start of the day, and this was all based on using the polling data as inputs to their models.
He didn't though, and that's my point. What you're saying is factually untrue, they haven't updated their prediction since election morning, and it sits at 71% Clinton [0] (Updated Nov. 8, 2016). If you don't believe that, then you can take a look at archive.is, which provides timestampped copies. This [4] is an archived copy from well before polls closed (3:30 PM), there are others from earlier in the day.
I don't know what led you to believe that it was a sure clinton win, but that just wasn't the case.
Clinton won the popular vote by somewhere between 2 and 3%. National polls from just before the election (also per 538, [1]):
+4, +2, +3, +4, +4, +4, +4, +4, +2, +3
Take Florida, a state trump won, here's polls taken in Novemeber [2]:
+1, -3, +0, +2, +1, -4
Take Pennsylvania [3], another close state. November polls again
+1, +2, +4, +6, +3, -2, -2, +0, +0, +2, +2
[0]: https://projects.fivethirtyeight.com/2016-election-forecast/ [1]: https://projects.fivethirtyeight.com/2016-election-forecast/... [2]: https://projects.fivethirtyeight.com/2016-election-forecast/... [3]: https://www.nytimes.com/elections/results/pennsylvania [4]: https://archive.fo/4EQGB
But I don't think you got my point either. The detail doesn't matter. Whatever that number was about, it was pretty clear that 90% was not the right number, I'm not even pro-trump and I was confused, imagine what others thought.
Also, it is not ok to be irresponsible just because you're using a "scientific method". This is what cigarette companies did to fund research that "prove" that smoking is healthy. And this happens increasingly more, because writing polarizing articles generate more shares and page views and money.
Lastly, I am not trying to talk politics here, and it's not even just about NYT. Nowadays for a lot of writers it's all about generating more page views. Again, I'm fine with it (even the "fake news" viral sites), but I was pointing out that it is hypocritical to claim that you're "the truth", when you do things that are biased.
If I win the lottery, is it misleading for people to state that my odds of winning were one in a million?
It's not misleading to say your odds of winning the lottery is one in a million because it IS one in a million, mathematically. NYT saying Hillary would win by 90% chance is NOT mathematics. Do you really think your analogy was adequate?
My point was that people believe statistics, just like you believe that because NYT did it, it would be scientific and you should believe it. But that's where the danger lies. And an influential publication such as NYT should be ashamed of themselves for misleading people by trivializing things down to just a percentage and feeding it to the world, in realtime.
I'm sure a lot of Trump fans who saw that poll on NYT that morning who didn't care for voting decided to go vote.
Actually yes, that is exactly what I'd like to find out more about. I'm asking why you are so sure that the NYT and other media publication odds were so wrong? Is it just that he won, therefore his odds must have been better than 10%? Most betting markets (which the HN set seems to put a lot of faith in) had Clinton as a 80ish % favorite (http://www.cnbc.com/2016/11/07/betting-sites-see-record-wage...), do you think they were a product of a misled public?
Again, that's how probabilities work. Unless the prediction was 100% Hillary win then a Trump win is possible. This isn't a new concept, it happens in sports all the time. Odds are offered for betting, and every now and then there are upsets. That doesn't mean the odds are nonsense.
What's the alternative? News organisations never even attempt to gauge whose campaign is more popular? I don't think that's realistic.
Was it? Maybe 90% didn't match up with your intuition, but NYT wasn't making that number up out of whole cloth. That's what the polls were saying, as analyzed by the NYT polling staff.
Maybe they were wrong (maybe they weren't-- things that have a 10% chance of happening happen all the time), but you certainly haven't demonstrated, or even really attempted to demonstrate, bias. All you've really said is:
* Trump won
* Your intuition told you he had a greater than 10% chance of winning before election day
> throughout the entire election cycle the narrative was NYT vs. Trump. News organizations and journalists should report stories but should not become the story.
It's important to remember that this narrative largely came (and continues to come) from Trump, and he benefited greatly from it.
No, they weren't, because everyone paying even a little bit of attention to the issues around aggregating polling numbers new that 538 had already dissected the problem with that long before the election—most prediction models were falsely assuming that variations in outcome from.the poll averages between different states were independent events when history shows that such deviations are strongly correlated. Which is why 538, working with essentially the same polling data as everyone else, had Clinton's chance of losing much higher than NYT and some other predictors.
> To me, THAT's the ultimate "fake news".
Predictions of the future are (and were presented as) analysis, not news. To be "fake news", it has to firsr pretend to be news, that is, reports of things that have occurred.
I think that's where the confusion lies. The majority of published polls and pundit calculations pointed that way, and it was earnestly interpreted by well-intentioned journalists that 90% of polls meant 90% probability. Perhaps I'm cutting a little too deep with Hanlon's razor here, but I think systemic biases are a more likely culprit than some kind of media conspiracy.
My own observation during the days leading up to the election was that her chances of winning were decreasing at a faster rate than could be reported with reliable polling data, though I still believed that she'd eke out a win.
I don't remember that at all. I remember the chances of winning, but that is not in any way a claim that she is winning by a large margin. In fact, reading the articles during the campaign and during election day, there was a lot of talk about even though polling data read one way, Trump wasn't out of it.
But yes, if you just read the headlines and didn't actually read the content, I could see why you'd say this.
And here's the page I was talking about: https://www.nytimes.com/elections/forecast/president
Now it says >95% Trump, but on that day it was the other way around--something like >95% Hillary.
That being said, predicting the outcome of an election with some 250 million potential voters based on a few hundred thousand polled individuals is a tricky game to play.
And, fwiw, your sort of political "objectivity" just doesn't exist. What you want is the sort of fake equivalence as in "Yesterday, 10 people died in an earthquake in Northern Italy, according to local accounts. But Jeff from Kansas writes on Twitter that there was no earthquake and the cause of death was the LHC's creation of a black hole. What's the truth? You decide! Back after this...".
It's like saying "Nobody is perfectly ethical. So trying to be ethical is just being fake."
Also you are using a funny example to make a point that's not relevant to this instance. That has nothing to do with news organizations siding with certain political party and pretending to be unbiased.
It wasn't just the New York Times, it was every single news outlet and every single poll. We have been running and studying elections for over 100 years, you would think, by now, that if we had any idea what we were doing, we would have long ago learned how to perform actual predictions using the data available to us.
When people break their legs, we can cure them 100% of the time because medicine has a strong answer for this problem based in thousands of years of medical science. Election polling and prediction is simply not in the category of "solved" problems.
If the statistics were really well understood...as some of the people arguing with you are claiming...WOULDN'T WE HAVE FIGURED THIS OUT BY NOW?
I have had these discussions about polls and statistics with my Liberal friends. Many of them are software engineers. Some of them even work in ML at large scale. They are utterly convinced that the data and statistics just need to be tweaked a little bit more and THEN they will be correct. To quote Donald Trump: WRONG!
There is a simple explanation for what happened that does not get into nit-picking statistical nuances. There is a simple explanation that does not allow people on the other side of the argument to bludgeon less educated opponents into silence by spewing technical jargon about polling data (which is really just a manipulation technique used to silence people by berating their intelligence).
The explanation is that the polling data was simply made up.
Or that many prediction models were created and only the ones favorable to the desired narrative were selected as being "Accurate" by people who are blinded by deep personal political bias.
This outcome scares people who prefer to see the world in a particular way.
People want to believe they aren't biased or that everything they read and see everyday is somehow "clean" or being presented by rational experts. That is a scary thought process...software engineers, in particular, cannot bear to believe that because it violates their underlying belief that the world operates in a logical way.
So instead of thinking like this, they crack open statistics textbooks and start reading chapter 4 at you. Its a defense mechanism to avoid reality.
There are direct financial rewards for telling people exactly what they want to hear. If Nate Silver and 538 consistently told people that Donald Trump would win, it is likely that their page-views would plummet into oblivion. Instead, the vast online hoards who like to be told whatever they want to hear and read news only to have their existing beliefs confirmed swarmed over Nate's websites, clicking on articles and gleefully watching the ads.
What is Nate Silver's punishment for being wrong over and over again? Nothing! There is no identifiable drop-off in his web traffic despite him and his team being wrong about everything this last election.
If what Nate Silver was doing was really "data journalism," shouldn't his following online have dropped off a cliff? It hasn't and it won't because what 538 is doing is not really backed by data and his readers and viewers are not discerning enough to care or believe that what they are reading is just opinion.
I am fairly disgusted by humanity at this point as a result.
Keep strong my brother, you are right. The people quibbling with you are living in an alternate reality where the media isn't incentivized by page views to gravitate towards narratives that result in more clicks. The media is dead.
You don't feel like you are oversimplifying a bit, and applying your own bias? Any pollster knows (and I realize you may ignore this point due to that opening bit) that there are margins for error as long as your sample size is any smaller than 100% of the population. Further, any pollster knows that your data will be skewed by how a question is worded.
The data wasn't made up, and each outcome was within the predicted margin for error. Many people will accuse the statistician of using large margins for error to cover any issues in the data, but that is straight from the opposite end of the spectrum of error.
> People want to believe they aren't biased or that everything they read and see everyday is somehow "clean" or being presented by rational experts. That is a scary thought process...
No one believes that everything they read is clean; anyone who does has (again) oversimplified the world. It isn't black and white. Every day, the margin for error is being examined, polls are being refined, questions are being tweaked. If the pollsters thought they had it all nailed down, why would they even be re-evaluating the method?
The only way to get 100% accurate data would be to poll 100% of the people who are going to vote -- and 0% of the people who aren't. Oddly, that is what happens on voting day -- at great expense, through great manpower, and with great effort. Pollsters simply don't have those kinds of resources.
> There are direct financial rewards for telling people exactly what they want to hear.
People do love to be reinforced, but again you are drastically oversimplifying a more complex issue. No matter what happens, no matter the outcome, people want to read the polls.
I mean, why do we even have them otherwise? So regardless of the error bars or margins, polls are going to keep happening; some will be correct, some won't. Most will fall within fairly narrow margins for error, but often the <50%> marker is in that margin -- so the opposite outcome could happen, even within the poll's own admitted rules.
> So instead of thinking like this, they crack open statistics textbooks and start reading chapter 4 at you. Its a defense mechanism to avoid reality.
Unnecessarily inflammatory, I think. The worst part about this rant is that the polls were so close to accurate -- especially if you count the popular vote, instead of the electoral college outcome. It all seems to be a symptom of a country that is, perhaps, too large and diverse for a federal government. I would argue for States' rights here, or say States should be more largely self governing -- but you do need a mechanism to get money from California (taxed $405B, received $343B in federal expenditures) to Kansas (taxed $9.9B, received $24.2B).
That was a bit of a tangent; the point is that the setup of the United States government, both from the State side and Federal side could use some work.
> What is Nate Silver's punishment for being wrong over and over again?
And what is his reward for how often he is right? He works in an industry with a large margin for error. Are you arguing that statistics should basically be abolished? Fivethirtyeight does far more than political polling, mind.
The other thing is relative; Nate Silver was far closer to the mark than any other publication, and his data were more robust. If you are arguing that Nate should lose traffic, every other organization (including those that argued for a Trump win based on similarly faulty statistics) should receive even more loss?
> If what Nate Silver was doing was really "data journalism," shouldn't his following online have dropped off a cliff?
But he was working with the data he had. Fivethirtyeight doesn't even do its own polls; it aggregates data from other polling organizations. Should Nate have made up the data? That is the exact opposite of what you are arguing, and I think your anger is misplaced.
> I am fairly disgusted by humanity at this point as a result.
If a set of polls being off by less than 3% is your threshold for a disgust in humanity, I am afraid your view is narrowed to the point of being useless. There are bigger things to worry about, at least as far as I am concerned.
I just wanted to point that out, in the end.
https://web.archive.org/web/20161101110545/http://www.nytime...
For me, the moment all my trust in NYT died was the election day. The front page had this interactive realtime story of how Hillary is supposedly winning by overwhelming margin, when it was very apparent that that's opposite of the truth. People kept questioning "where the hell is this data coming from?".
I believe Newspapers should try to play as much neutral role as possible, but throughout the entire election cycle the narrative was NYT vs. Trump. News organizations and journalists should report stories but should not become the story.
As someone who just wanted to learn what REALLY is going on, I had (and still have) hard time believing anything they say anymore. Other conservative publications at least don't claim to be neutral. A publication shouldn't claim to "tell the truth" and do a whole TV ad about it if they are clearly biased and they're also aware of this.
I know they're being provocative because this sells, and they need to make money, and it's getting harder to make money with newspaper. But they've crossed the line.
People keep talking about "fake news", but what's really dangerous is not some viral website that write some funny photoshopped story. What's really dangerous is influential news organizations like NYT doing deceptively objective-sounding pieces with narratives that mislead the public.
By now I think a lot of people know it's very possible to take a same piece of reality and write completely different versions of it, just by framing them differently. Because of that I have hard time believing anything online anymore, especially the influential ones. This is sad because it used to be the job of journalism to fight against injustice, but nowadays it's more about generating more page views and getting more subscribers, which led to people losing faith in journalism.