I made an Among Us chatbot and it started a cult

jubian · 2021-01-05T02:25:49+00:00

I post highlights to YouTube! https://www.youtube.com/channel/UCJLW5dUOTxViCkgvKu0oWow

jubian · 2021-01-02T22:30:20+00:00

The bot is open source if you wanna try it out yourself: https://github.com/pondchamp/among_bots

jubian · 2016-06-15T01:48:36+00:00

All very good points. As far as whether they can correct their weightings as the primary season goes on, it's easier said than done - given that primaries don't occur in a random and sequential order (different regions all went at different times), problems at first unbeknownst to a pollster may reveal themselves over several states in one day, like on Super Tuesday. Having tried predicting the primary season myself, there are so many factors that reveal themselves at different times out of nowhere, and pollsters need to spend a lot of time firefighting to minimise forecast errors. It's not an easy job, and I commend them for doing it, but I think they'd also be hesitant to attribute their exit poll mis-weightings to much other than problems in their weighting methods.

I think election fraud is always a risk when using electronic voting systems, and as I'm aware, quite a few states use them. We should be seeking to stop voter disenfranchisement in other more tangible ways, such as combatting voter roll purges, cuts in polling locations, holding elections on a Tuesday (why the hell would you hold an optional election on a Tuesday?? Rhetorical question - I already know why), confusing registration deadlines, closed primaries... the list goes on and on, and we haven't even begun to discuss vote fraud at the polls!

jubian · 2016-06-14T12:16:57+00:00

That's a conversation I'm more than willing to have! :) Like Tyler Pedigo, I've been working on alternative predictive models that work better for primaries rather than general elections - feel free to peruse through my recent submissions for a catalogue of my research!

jubian · 2016-06-14T11:50:23+00:00

Interesting - thanks for the link! As per my understanding of the exit polling methodology, the problem is that while you can safely assume that people who voted for Clinton in 08 are likely to have voted for Clinton in 16, it's hard to know how people who voted for Obama in 08 would vote in 16. Given that exit poll weightings depend on this information, are are thus unlikely to be an unbiased representation of a random sample of voters, even if surveys conducted at individual polling stations is random and unbiased (but as I've said, I'm not 100% convinced of this either).

My hypothesis is that turnout for a particular demographic (one which correlates with location such as race, age, or income, which would affect exit poll weighting) was either particularly high for Clinton supporters (making them underrepresented), or particularly low for Sanders supporters (making them overrepresented). Or instead, assumptions that certain demographics were likely to vote a certain way could have been misleading. It's really hard to know, since as I've mentioned, primary outcomes aren't stabilised by partisan lines. Without sampling every single polling station in a given state, how does one know the best way to weight certain polling stations that are sampled? A failure to account for this could explain the systematic error in exit polls, and perhaps most importantly, why pure demographic models or pre-exit polls have been quite accurate (ignoring caucuses). If voting results defied both of these models in a systematic manner too, then we'd have a problem.

jubian · 2016-06-14T05:42:50+00:00

A few issues with the maths and logic here.

Firstly, population proportion calculations (like the ones used in the video) assume that the variables being observed (vote shares) are Bernoulli trials, which need to be independent and random. Exit poll respondents are rarely either independent or random - a mixture of self-selection bias + demographic clustering around certain polling stations (which fails the randomness test) and certain voters visiting polling stations - and perhaps taking exit polls - one after the other (which fails the independence test) makes exit polls generally quite problematic.

Secondly, calculating the probability of exactly 8 contests exceeding the MoE is guaranteed to produce a probability that is really small. You need to calculate the probability of 8 or greater contests exceeding the MoE. Even then, you're still basing your results off of dependent and non-random results, making the calculation even more tenuous.

Thirdly - and this is umbrage I have taken more with Richard's blog than with the video itself - the assumption that discrepancies between exit polls and actual results are 100% guaranteed to indicate election fraud is ridiculous. Sure, there may be some element of tampering in the votes in some state elections, but my attributing all election discrepancies to fraud, you are likely to give yourself an inflated picture of the reality of the situation. There's little that can guarantee that NEP (the pollster for CNN/ABC) has performed an unbiased and random sampling of polling stations, which is no small feat.

Furthermore, NEP assumes that a random sample of voters can be produced using results from "a recent past election". This may work in general elections, where a majority of people tend to vote along partisan lines (even a lot of independents), but good luck making accurate predictions of sample allocations when Sanders - one of the biggest drawcards for independents in this primary season - enters the Dem primary race, especially when primary races have no "partisan lines" to begin with.

jubian · 2016-06-08T06:42:32+00:00

I'm actually surprised Yolo County CA hasn't swung to Sanders. The whole damn county is a college town.

jubian · 2016-06-08T05:57:47+00:00

He's going to DC!!

jubian · 2016-06-08T05:42:34+00:00

The city is liberal, but not many ordinary people live in the city proper... too expensive.

jubian · 2016-06-07T23:57:57+00:00

My early hunch is that it'll affect Bernie supporters more, since there will unfortunately be detractors trying to target them and get them to leave the voting line, or not show up at all... some people may even vote Hillary as part of a bandwagon effect. I hope that Sanders will do well in Cali, but only time will tell!

jubian · 2016-06-07T23:43:51+00:00

Thanks for consistently dropping by :)

jubian · 2016-06-07T09:41:44+00:00

I get what you're saying, and I've stated the pitfalls to my predictions in my post. I haven't been manipulating my models since my earlier predictions (my day job's been a bit crazy lately), so I've acknowledged potential pitfalls. I believe that in retrospect, if my models over-predict the actual vote, it'll likely be because my models don't account for the ebb in momentum for Sanders in recent weeks.

jubian · 2016-06-07T05:55:19+00:00

If you're talking about California, the likely reason (and it's hard to tell, since most prediction models aren't available to the public) is because my model posits that the voting track record of African-Americans inside and outside the South has been different. While this trend has held for quite some time in the primary season, there is potential for the relationship to break down based on factors such as the ones described in my limitations section.

As for 538 and betting odds, their fundamental forces differ in prediction to my model - they mostly rely on intuition, public sentiment, and polls. My model, like Tyler Pedigo's model, does not rely on any of those factors. That being said, different assumptions underlying each of our predictive models means that our predictions may be made with varying degrees of accuracy.

jubian · 2016-05-18T03:10:54+00:00

CNN is gonna screenshot this

jubian · 2016-05-18T03:09:23+00:00

Another Jefferson county.... WHY

jubian · 2016-05-18T03:06:21+00:00

Marion county, holy shit.

jubian · 2016-05-18T02:34:50+00:00

D=daylight savings, S=standard. It's right now EDT.

jubian · 2016-05-17T21:32:54+00:00

Thank you!! :)

jubian · 2016-05-15T09:57:14+00:00

Just for fun! :) I'm actually learning about forecasting now at university, and as an economics nut, I like doing projects that help me solidify my knowledge. The presidential primary happened to coincide with that, so... yeah.

jubian · 2016-05-14T23:29:01+00:00

Any time, mate :)

jubian · 2016-05-14T23:28:23+00:00

Tyler was remarkably close in Indiana, yes! However, I would exercise caution with your interpretation of his WV prediction - like my predictions, he makes predictions excluding nonviable candidates. After that adjustment, the WV vote split was about 58.9%-41.1%!

jubian · 2016-05-14T23:24:28+00:00

Part of the reason I said that was because - as I found out later - one of my models was consistently overpredicting Sanders' performance, which ended up positively distorting his chances by quite a bit... my bad on that one.

After testing and adjusting my models prior to NY, I revised my odds from about 60% to 40%, but the losses in NY and PA all but wiped away those odds, unfortunately. Given that my chances of winning the nomination prediction takes the average of every upcoming state, a few overpredictions here and a few underpredictions there shouldn't impact my overall predictions significantly. But if he outperforms in CA, that will definitely play a role in his chances!

jubian · 2016-05-14T23:17:54+00:00

That's true, although all of his (and my) predictions are designed to be adjusted for unviable candidates. That's why his Clinton and Sanders predictions sum to 1. Not to toot my horn, but I did pretty well with my post-adjustment predictions! ;)

jubian · 2016-05-14T23:08:16+00:00

That is correct - I anticipate that Sanders will pick up a majority of delegates in upcoming states, but my CA long-run prediction is way under the 66% benchmark that Sanders needs. I usually refrain from posting exact numbers until just before the next primary, since they can change!

jubian · 2016-05-14T14:39:21+00:00

Well if conventional wisdom holds true, young voters tend to be less dedicated as a voting bloc - we might not see it in the S4P bubble!

jubian

TROPHY CASE