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Surprisingly popular

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Re: Surprisingly popular

#22
Looks like an idea for a semi-supervised ensemble method for machine learning:

Prepare two equally sized ensembles of classifiers, let's call them A and B.

1. Train each classifier in ensemble A on labelled data to predict does a picture contains a cat.

2. Take some other unlabelled dataset and collect answers from classifiers from A for each picture from this dataset.

3. Train each classifier in ensemble B to predict average answer of classifiers from A for each picture from the unlabelled dataset.

Then for a picture from the test dataset it would be possible to get answers from ensemble A and from ensemble B and calculate what would be the surprisingly popular answer.

Re: Surprisingly popular

#23
post #17

Let's look at another toy example, using made-up numbers: Q: Is the earth flat? Yes: 10% No: 90% Q: What do you think most people will respond to that question? Yes: 3% No: 97% Analysis: Yes: 10% - 3% = 7% No: 90% - 97% = -7% Conclusion: The earth is flat, I guess ;)

Q: Is the earth flat? -> "Not controversial enough..." (nowadays, in 2019) ie. it does not fit the "surprisingly popular" definition because it isn't popular. There's just a few loudmouths who make it seem like that (combined with a bunch of jokers who joke about it). Hence you don't get many people who will argue most people will respond Yes. You could regard that as a flaw, I see it as a feature.

Re: Surprisingly popular

#24
post #17

Let's look at another toy example, using made-up numbers: Q: Is the earth flat? Yes: 10% No: 90% Q: What do you think most people will respond to that question? Yes: 3% No: 97% Analysis: Yes: 10% - 3% = 7% No: 90% - 97% = -7% Conclusion: The earth is flat, I guess ;)

Good example.

Guess this technique may also detect facts that are involved in common conspiracy.

Re: Surprisingly popular

#26
post #17

Let's look at another toy example, using made-up numbers: Q: Is the earth flat? Yes: 10% No: 90% Q: What do you think most people will respond to that question? Yes: 3% No: 97% Analysis: Yes: 10% - 3% = 7% No: 90% - 97% = -7% Conclusion: The earth is flat, I guess ;)

This also shows my problem with the way the concept is presented.

The correct answer to the second question is "No". That is what most people would say. So technically, if we saw Yes:0, No:100, that would just mean everyone knows what they popular choice is.

What they want to ask is "How many people would say the answer is "No"?" Then if the answers are far afield, we can say whether or not an answer is surprisingly popular.

So in the article and with your example, the second question isn't actually a reflection of the proportions of the first. They're kind of disconnected.

Re: Surprisingly popular

#27

The capital is not Philadelphia, it's Harrisburg. So the idea must be that most people think they are right and others will agree with them, but there are people who get it right and know that others get it wrong, and they are responsible for the difference in scores.

Thanks, I read the article multiple times and couldn't really understand why someone would give the wrong answer and then assume that most people would give the right answer (I didn't know Pennsylvania wasn't the capital of Philadelphia).

> I didn't know Pennsylvania wasn't the capital of Philadelphia

Yes you did. :)

Re: Surprisingly popular

#28

Earlier quoted context omitted.

Thanks, I read the article multiple times and couldn't really understand why someone would give the wrong answer and then assume that most people would give the right answer (I didn't know Pennsylvania wasn't the capital of Philadelphia).

> I didn't know Pennsylvania wasn't the capital of Philadelphia Yes you did. :)

You know what I meant :(

Re: Surprisingly popular

#30
post #17

Let's look at another toy example, using made-up numbers: Q: Is the earth flat? Yes: 10% No: 90% Q: What do you think most people will respond to that question? Yes: 3% No: 97% Analysis: Yes: 10% - 3% = 7% No: 90% - 97% = -7% Conclusion: The earth is flat, I guess ;)

I think this a fair criticism which you haven't well explained, that a minority expert might be minority misled.
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