Mobs, Filter Bubbles and Democracy

You know I love to ask “why”? And last Tuesday provided me with the mother of all “whys”. I know there will be a lot of digital ink shed on this – but I just can’t help myself.

So..why?

Eight years ago, on Mediapost, I wrote that we had seen a new type of democracy. I still think I was right. What I didn’t know at the time was that I had just seen one side of a more complex phenomenon. Tuesday we saw another side. And we’re still reeling from it.

It’s not the first time we’ve seen this. Trump’s ascendancy is following the same playbook as Brexit, Marine Le Pen’s right winged attack in France and Rodrigo Duterte’s recent win for the presidency of the Philippines. Behind all these things, there are a few factors at play. Together, they combine to create a new social phenomenon. And, when combined with traditional democratic vehicles, they can cause bad things to happen to good people.

The FYF (F*&k You Factor)

Michael Moore absolutely nailed what happened Tuesday night, even providing a state-by-state, vote-by-vote breakdown of what went down – but he did it back in July. And he did it because he and Trump are both masters of the FYF. Just like you can’t bullshit a bullshitter – you can’t propagandize a propagandist. Trump had borrowed a page out of Moore’s playbook and Moore could see it coming a mile away.

The FYF requires two things – fear and anger. Anger comes from the fear. Typically, it’s fear of – and anger about – something you feel is beyond your control. This inevitably leads to a need to blame someone or something. The FYF master first creates the enemy, and then gives you a way to say FY to them. In Moore’s words, “The Outsider, Donald Trump, has arrived to clean house! You don’t have to agree with him! You don’t even have to like him! He is your personal Molotov cocktail to throw right into the center of the bastards who did this to you!”

What Michael Moore knew – and what the rest of us would figure out too late – was that for half the US, this wasn’t a vote for president. This was a vote for destruction. The more outrageous that Trump seemed, the more destructive he would be. Whether it was intentional or note, Trump’s genius was in turning Clinton’s competence into a liability. He succeeded in turning this into a simple yes or no choice – vote for the Washington you know – and hate – or blow it up.

The Threshold Factor

The FYF provides the core – the power base. Trump’s core was angry white men. But then you have to extend beyond this core. That’s where mob mentality comes in.

In 1978, Mark Granovetter wrote a landmark paper on threshold models of behavior. I’ll summarize. Let’s say you have two choices of behavior. One is to adhere to social and behavioral norms. Let’s call this the status quo option. The other is to do something you wouldn’t normally do, like defy your government – let’s call this the F*&k You option. Which option you choose is based on a risk/reward calculation.

What Granovetter realized is that predicting the behavior of a group isn’t a binary model – it’s a spectrum. In any group of people, you are going to have a range of risk/reward thresholds to get over to go from one behavioral alternative to the other. Being social animals, Granovetter theorized the deciding factor was the number of other people we need to see who are also willing to choose option 2 – saying F*&k you. The more people willing to make that choice, the lower the risk that you’ll be singled out for your behavior. Some people don’t need anyone – they are the instigators. Let’s give them a “0”. Other people may never join the mob mentality, even if everyone else is. We’ll give them a “100.” In between you have all the rest, ranging from 1 to 99.

The instigators start the reaction. Depending on the distribution of thresholds, if there are enough 1, 2, 3’s and so forth, the bandwagon effect happens quickly, spreading through the group. It isn’t until you hit a threshold gap that the chain reaction stops. For example, if you have a small group of 1’s, 2’s and 3’s, but the next lowest threshold is 10, the movement may be stopped in its tracks.

Network Effects and Filter Bubbles

None of what I’ve described so far is new. People have always been angry and mobs have always formed. What is new, however, is the nature of this particular mob.

As you probably deduced, the threshold model is one of network effects. It depends on finding others who share similar views. It you can aggregate a critical mass of low thresholds; you can trigger bigger bandwagon effects – maybe even big enough to jump threshold gaps.

Up to now, Granovetter’s Threshold model was constrained by geography. You had to have enough low threshold people in physical space to start the chain reaction. But we live in a different world. Now, you can have a groups of 0s, 1s and 2s living in Spokane, Washington, Pickensville, Alabama, and Marianna, Florida and they can all be connected online. When this happens, we have a new phenomenon – the Filter Bubble.

One thing we learned this election was how effective filter bubbles were. I have a little over 440 connections in Facebook. In the months and weeks leading up to the election, I saw almost no support for Trump in my feed. I agreed ideologically with the posts of almost everyone in my network. I suspect I’m not alone. I am sure Trump supporters had equally homogeneous feedback from their respective networks. This put us in what we call a filter bubble. In the geographically unrestricted network of online connections, our network nodes tend to be rather homogeneous ideologically.

Think about what this does to Granovetter’s threshold model. We fall into the false illusion that everyone thinks the same way we do. This reduces threshold gaps and accelerates momentum for non-typical options. It tips the balance away from risk and towards reward.

A New Face of Democracy

I believe these three factors set the stage for Donald Trump. I also believe they are threatening to turn democracy into never ending cycle of left vs. right backlashes. I want to explore this some more, but given that I’ve already egregiously exceeded my typical word count for Online Spin, we’ll have to pick up the thread next week.

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