From Brexit to Climate Change: How Social Networks Lead to Echo Chambers
The structure of social networks can shed light on society in many ways. From racism to politics to religious extremism, the complexities of how social networks form and operate can teach us a lot about how certain aspects of society work.
But before I explain why, let’s review what I covered in the past two essays about how social networks are created and maintained.
First we looked at the structure of social networks and how people are either weak ties or strong ties. Weak ties, or acquaintances from other networks, are more likely to bring novel information to you and your network. They act as bridging ties across structural holes, transmitting new knowledge, ideas, and contacts. Structural holes — gaps in networks — stop the flow of value, and bridging them creates value.
Next we learned about role sets and status sets, which are the interrelationship any individual has with other individuals who are different from them. People with very limited social networks and no weak ties end up with simple role sets in which they engage primarily with other people who are very similar to themselves. They do not develop the social skills needed to navigate around networks, where empathy and an ability to see things from other people’s perspectives are essential for making relationships with people like you and avoiding conflict.
Finally, we discussed how social capital is the network equivalent of financial and human capital. Social capital can be the currency that is accrued and spent within networks, analogous to favors. It is also the trust that holds networks together, which in itself is a form of value — someone who is highly trusted is also highly valued.
Networks rich in social capital work together well and have clear norms that ensure everyone works to their mutual advantage. When there is strong social capital, these norms are easily policed because people communicate and work together.
When people breach the norms they are sanctioned, and when they act within them, they are rewarded. Sanctions and rewards can come in many forms, but in a dynamic network where links change rapidly, severing links is a powerful form of sanction, and rewarding with more links is an incentive to play ball.
What Does This All Mean?
It’s been observed that networks with strong internal capital and a lack of weak ties tend to become introverted, corrupt, and subject to conspiracy theories. The corruption is a result of the strong internal social capital, meaning that people stick to strong internal codes of conduct and have very strong loyalties. But without the weak ties, and therefore a wider context, those loyalties to the strong ties in their network become more important than, for example, the wider social good or adherence to laws.
Combining the structure of social networks with the sociological concepts of role sets, and social capital begins to shed light on society in many ways.
It goes some way to explain why some societies are successful while others are failing. It gives insight into how our worlds involve such polarity of ideas when it comes to politics, climate change, nationalism versus internationalism, racism, and religious extremism. It does not provide answers, but it does give clues to where the answers may be.
If people develop only simple role sets, they get stuck in social networks that have strong internal social capital and no weak ties. They develop myopic ideas, cannot unpick conspiracy theories, and lack empathy with others, because they are not exposed to other people or other ideas.
They cannot see the world from other people’s perspectives. This leads to phenomena like racism, religious hatred, and a lack of trust in “the establishment,” science, media, and other things that represent other role sets or status sets.
Social Networks and Contagious Ideas
In fact, the complex dynamics of social networks are powerful influencers on all aspects of ourselves and our societies. Some chilling research showed that if someone in a couple’s close social network gets divorced, it increases the likelihood of that couple also getting divorced. The logic being that seeing other couples “give up” on their marriage affects the extent to which couples will be willing to fix the tribulations in their own marriage.
The spread of fashions and how ideas take off through networks are discussed in Malcolm Gladwell’s book The Tipping Point. Academics Nicholas Christakis and James Fowler have studied this in various contexts, including happiness, loneliness, and smoking. What they wrote about happiness and loneliness is so striking, it is worth quoting in full:
Clusters of happy and unhappy people are visible in the network, and the relationship between people’s happiness extends up to three degrees of separation (for example, to the friends of one’s friends’ friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile (about 1.6 km) and who becomes happy increases the probability that a person is happy by 25% (95% confidence interval 1% to 57%). Similar effects are seen in co-resident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next door neighbours (34%, 7% to 70%)…People’s happiness depends on the happiness of others with whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.
Imagine the policy and social implications of acknowledging that happiness is infectious. If happiness, health, and well-being are collective phenomena, and we understand how the structure of social networks can inhibit or encourage the spread of ideas, how should that inform how individuals and policymakers look at personal and societal problems? And conversely, the same applies loneliness, also over three degrees of separation:
Loneliness occurs in clusters, extends up to 3 degrees of separation, is disproportionately represented at the periphery of social networks, and spreads through a contagious process. The spread of loneliness was found to be stronger than the spread of perceived social connections, stronger for friends than family members, and stronger for women than for men.
In all the aspects of behavior and emotions Christakis and Fowler explored, they found a spread through three degrees of a network, which is a considerable distance. They were able to see smoking and nonsmoking happening in clusters within networks, and other research has shown that this applies to obesity, propensity toward suicide, and a variety of damaging behavior.
This insight into the power of networks on everything from opportunities to happiness shows the importance of networks, but also the importance of understanding how they function and being able to describe this accurately.
Equipped with the language of Mark Granovetter’s work on the strength of weak ties, and Ronald Burt’s work on structural holes, we see that having plenty of weak bridging ties means you have a lot of access to other networks, which are clusters of other ideas, knowledge, and opportunities, and if you stand close to structural holes, you are exposed to a wider range of ideas that challenge your own, as well as developing power as a broker of that information. Furthermore, these broader and more open networks provide escape routes from the clustering of negative influences, from loneliness to obesity.
So, when our networks collapse and we end up highly embedded within one that is rich in strong ties and devoid of weak ties, we are no longer exposed to other ideas that challenge our own, and we are surrounded by people who are all exposed to the same limited set of information and ideas, which become self-reinforcing.
Such closed networks can affect our happiness, depression, loneliness, tendencies toward suicide, smoking, and being healthy. All of this starts to explain the way our societies have clusters of disadvantaged people who lack hope, live unhealthy lives, and find it hard to escape from social ghettoes.
Furthermore, at a global level, societies that are dominated by strong ties, with too much internal social capital, end up with norms that push people to accept just one set of ideas and not challenge them. The group will sanction heavy detractors from their accepted narratives, and there will be very little debate or discussion, which instead becomes replaced with reinforcement and confirmation.
This technical description fits well what exists within dictatorships, where the sanction is state-sponsored, but increasingly it also describes the information echo chambers we are seeing in current politics.
With the slide of a country into dictatorship or economic decline, there is a problem that those who can leave do leave, which then accelerates the problem as those who remain become increasingly poorer in weak ties and form a strong-tie network with strong internal social capital (necessary for survival during a crisis). With extremist politics, eventually all you have left are those who agree with the core or those who are unwilling to disagree.
Are Tech and Social Media Good, or Making This Worse?
Technology is an interesting aspect of this effect on social networks—in particular, the ideological isolation of the right. As we have learned over the past year, the algorithms behind Facebook and other tech and social media sites have been creating self-reinforcing feedback loops in which people increasingly see only information that they will like and that their closest friends like.
This is technology driving social networks to lack weak ties and have strong internal social capital. Think about what happens when you disagree with the consensus around a Facebook post: You are sanctioned by tie dissolution (people unfriend you).
A bridging weak tie in a web context is a link to a source of information that you might not normally look at, you may not agree with, and challenges your ideas. Facebook and Google algorithms do the opposite: They show things we will like and agree with, so they are basically erasing our weak, bridging ties, at least in our digital networks.
To keep our minds open, we need to be much more aware of the underlying science of our social networks. It is important to:
- Understand whether something represents a bridging weak tie or is enforcing our strong ties;
- Know where our social capital lies, and how it influences our actions within our social networks; and
- Recognize where our own networks have developed norms, and how they are policed.
This also forms the basis of an understanding that could be used to try to reopen the dangerously closed information bubbles; for example, the right wing in the United States and Europe, not to mention what is happening in Russia, China, Turkey, North Korea, and so many other countries that are censoring the internet and building state-sponsored information bubbles around their citizens.
Echo chambers are basically the knowledge outcome of a strong-tie network with no weak ties to bridge over structural holes. Information within an echo chamber is redundant and repetitive. People do not receive novel information, and their trust is internalized within the network — they trust their own sources and not new sources (strong internal social capital). They do not meet people who challenge their ideas (weak ties), and they mainly meet people who share and enforce their ideas (strong ties).
Solutions, therefore, lie in creating weak ties, bridging structural holes, breaking up excessive internal social capital, and building new social capital across weak ties. This explains why so many peace and reconciliation processes involve things like people playing football, eating together, and sharing life experiences. This creates bridging ties between networks, develops social capital, and helps people realize they aren’t so different. History is full of this.
History is also full of societies that cut their weak ties, isolating people from information that gives them a context from within for judging their own leaders or challenging propaganda. Think of North Korea, or Stalin’s Soviet Union.
Where there are walls, censorship, and propaganda, people rapidly collapse into strong-tie networks with internal social capital, no weak ties, and no bridging. They rely heavily on their immediate network of close friends and family for survival, they do not trust anyone else, and they no longer know what is really happening around them beyond this cluster of strong ties.
Knowing how these structures work can provide us with clues to solving some of these big problems.