A sociophysics professor predicted the win of Donald Trump in 2016 against Clinton. He didn't believe his own prediction, and was shocked to see it come true !

He predicts his win again. Here's why. And here's why the anti-Trump campaigning is HELPING Trump ! 🧵
He says that Trump's victory is not an accident, but it is not linear so we can model it, but the model will be more complicated. The prof is Serge Galam and the field is sociophysics.

Yes, they only make terrible figures. I am sorry.

Here's how they model it:
He says that Trump's victory is not an accident, but it is not linear so we can model it, but the model will be more complicated. The prof is Serge Galam and the field is sociophysics. Yes, they only make terrible figures. I am sorry.Here's how they model it:
He says that Trump's victory is not an accident, but it is not linear so we can model it, but the model will be more complicated. The prof is Serge Galam and the field is sociophysics. Yes, they only make terrible figures. I am sorry.Here's how they model it:
Let's say people must choose between A and B.

People can be affected by discussing with each other & by external factors like an economic recession or a pandemic

In the model we ignore external factors & we say that the situation is at equilibrium.
We use a poll to find out what people plan to vote at the beginning. We call P0 the % of people who'll vote for A.

Now, there is three types of people: the contrarians, the inflexibles and the floaters (who can change their mind).
The field has physics in the title so we are going to simplify things. People can meet up in groups of 2-6 people and discuss politics. In that case, we assume that the floaters will align themselves with the majority opinion at the end. Each time.

The groups are random.
We now have a tipping point. If the % of people for A is above the tipping point, the floaters will be more and more for A. If it's less, less and less.

The more discussions, the stronger the effects.

If we only have groups of 3 people, the tipping point is 50% (easy).
But what if there is equality in the discussion group ? What do the floaters do ?? We can't use physics, obviously. 😅

Psychology tells us that in cases where we don't have info that weighs in one direction... We tend to activate some stereotypes and use them to decide !!!
Now people tend to be against reforms if they don't have an argument for the structural change. They prefer what they already know.

But they tend to be for novelty and fashionable stuff (in tech for example).
Now people tend to be against reforms if they don't have an argument for the structural change. They prefer what they already know. But they tend to be for novelty and fashionable stuff (in tech for example).
Now people tend to be against reforms if they don't have an argument for the structural change. They prefer what they already know. But they tend to be for novelty and fashionable stuff (in tech for example).
Aaaaand they have little stereotypes about groups of people. There's the classic (class disdain, sexism, homophobia, racism, etc.) but also more local or subtle ones.

(hihi, frog)
Aaaaand they have little stereotypes about groups of people. There's the classic (class disdain, sexism, homophobia, racism, etc.) but also more local or subtle ones.(hihi, frog)
Aaaaand they have little stereotypes about groups of people. There's the classic (class disdain, sexism, homophobia, racism, etc.) but also more local or subtle ones.(hihi, frog)
💡Serge Galam's intuition is that if we get too much info, & we can't decide (= a tie in the group), we have to rely on another decision mechanism... And the stereotypes that are activated (not all of them) come into play.

▶️ Too much info + activated bias = decision with bias
Serge Galam's intuition is that if we get too much info, & we can't decide (= a tie in the group), we have to rely on another decision mechanism... And the stereotypes that are activated (not all of them) come into play. Too much info + activated bias = decision with bias
Serge Galam's intuition is that if we get too much info, & we can't decide (= a tie in the group), we have to rely on another decision mechanism... And the stereotypes that are activated (not all of them) come into play. Too much info + activated bias = decision with bias
The model is quite simple. Let's throw math at it.

If we only have groups of 4, when they have a tie, they'll shift towards the bias. Now the tipping point has massively changed !!
The model is quite simple. Let's throw math at it. If we only have groups of 4, when they have a tie, they'll shift towards the bias. Now the tipping point has massively changed !!
The model is quite simple. Let's throw math at it. If we only have groups of 4, when they have a tie, they'll shift towards the bias. Now the tipping point has massively changed !!
For an opinion agreeing with the bias, it is enough to have 23% of people who agree with it at the start!! And if we discuss enough, the floaters will be convinced!

If the opinion goes against the bias, you need 77% of people who agree ! Else its popularity decreases in time.
For an opinion agreeing with the bias, it is enough to have 23% of people who agree with it at the start!! And if we discuss enough, the floaters will be convinced!If the opinion goes against the bias, you need 77% of people who agree ! Else its popularity decreases in time.
For an opinion agreeing with the bias, it is enough to have 23% of people who agree with it at the start!! And if we discuss enough, the floaters will be convinced!If the opinion goes against the bias, you need 77% of people who agree ! Else its popularity decreases in time.
What Trump did so successfully in 2016 is

▶️ Drown us information so we can't decide
▶️ Make us discuss with each others more
▶️ Activate the biases that favored him
💡 He's picking which biases to activate, it's not random!
Let's say the polls say 50&-50% (as usual).

You can change the tipping point, even if you lose supporters. You just need to always have enough supporters to stay above it.

Then make people talk & regain your advantage.
Now Trump could play dirty when Clinton couldn't. No one cares anymore.

Now Biden can promote a fear of Trump.
And Trump can promote a fear of Biden.

So who's going to have an effect ? The hard core pro-Trup & the hard-core anti-Trumps !
Now Trump could play dirty when Clinton couldn't. No one cares anymore.Now Biden can promote a fear of Trump.And Trump can promote a fear of Biden. So who's going to have an effect ? The hard core pro-Trup & the hard-core anti-Trumps !
Now Trump could play dirty when Clinton couldn't. No one cares anymore.Now Biden can promote a fear of Trump.And Trump can promote a fear of Biden. So who's going to have an effect ? The hard core pro-Trup & the hard-core anti-Trumps !
The model says that if you have enough inflexible voters for Trump (more than 17% of people)... The chance for Biden disappears ! Now matter his initial support!🤯

If you have the same numbers of inflexibles on each side, the vote move towards 50-50 no matter where it starts!🤯
Both Biden & Trump must have the same strategy:
▶️ Get more & more inflexible supporters!
▶️ Increase fear to activate prejudices in your favor!
▶️ Keep the discussion going to convince people who doubt.

And anti-Trumpers are not pro-Bidens... Which favors Trump.
Both Biden & Trump must have the same strategy: Get more & more inflexible supporters! Increase fear to activate prejudices in your favor! Keep the discussion going to convince people who doubt.And anti-Trumpers are not pro-Bidens... Which favors Trump.
Both Biden & Trump must have the same strategy: Get more & more inflexible supporters! Increase fear to activate prejudices in your favor! Keep the discussion going to convince people who doubt.And anti-Trumpers are not pro-Bidens... Which favors Trump.
This thread presented Prof. Serge Galam's research at @CNRS @INP_CNRS. It comes from a talk organized by Surajit Sen @drsoliton from @UBuffalo.

Video here:
This thread presented Prof. Serge Galam's research at @CNRS @INP_CNRS. It comes from a talk organized by Surajit Sen @drsoliton from @UBuffalo.Video here:
This thread presented Prof. Serge Galam's research at @CNRS @INP_CNRS. It comes from a talk organized by Surajit Sen @drsoliton from @UBuffalo.Video here:
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