> [!summary] Progressive Summary # Structured Notes ## Definitions ## Chapter Summaries ### Introduction The author is a social scientist whose research area is social networks. He argues that our theories of social change have been erroneously based on viral infection as a metaphor, and presents a more nuanced theory about a process called complex contagion. The main idea is that successful social change is not about information, but about norms. Social networks are not pipes through which ideas and behaviours flow. They are prisms that determine how we see those ideas and behaviours. Network bias is about how our networks distort our beliefs and norms. ### Chapter 1 - The Myth of the Influencer: The (Un)Popularity Paradox People only adopt new social gestures, such as a new handshake, when they are sure that others are going to use the new gesture. So paradoxically, the more socially connected someone is, the less likely they are to adopt a new gesture. This is known as a coordination problem. In 2008, physicist Lada Adamic and data scientists Eytan Bakshy and Brian Karrer did research on social networks. They found that we are more influenced by the percentage of people we know who are doing something, rather than the total number. Someone who knows 500 people is 10 times less likely to adopt something new than someone who knows 50 people. A social star, someone who is extremely well-connected, is more exposed to countervailing influences and the inaction of others. Therefore the periphery of a network is an easier place for social innovation to take hold. Columbia University sociologist Paul Lazarsfield coined the term *opinion leaders* in 1944, thus becoming responsible for an enduring myth in marketing. He published an influential paper in 1955. This myth was popularised by Malcolm Gladwell's phrase "law of the few". It says that a small number of special people are responsible for spreading new ideas. The law of the few works when you're spreading news or information. But it falters when it comes to social behaviour. Highly connected people can become roadbloacks in these scenarios. They become the very last step in social change. For social change, rather than look for special people, we look for special places. ### The Myth of Virality: The Unexpected Weakness of Weak Ties Mark Granovetter's 1970s paper, "The Strength of Weak Ties", is the most cited paper in all of sociology. The people we have strong ties to have overlapping networks. There's a lot of redundancy. That makes strong ties relatively inefficient at spreading information or ideas. In 1967, Stanley Milgram discovered that an average of six degrees separate people in America. Granovetter discovered why. It was weak ties. Granovetter's ideas come from the science of infectious diseases. But norms and technologies such as Twitter and Facebook spread through networks of strong ties. ### Chapter 3 - The Myth of Stickiness: Why Great Innovations Fail The Grapefruit problem - when two things that are normally good are put together, they can become toxic, like Lipitor and grapefruit juice Google Glass combined awareness and differentiation, and these two things backfired. Everyone knew about it, but only techies were wearing it. Other people started calling them Glassholes, because it was seen as surveillance technology for the rich. ### Chapter 4 - How Change Happens: The Discovery of Complex Contagions There are 4 types of resistance to change: 1. Coordination - when it requires a lot of people doing the same thing together 2. Credibility - when an innovation seems risky in terms of effectiveness or safety 3. Legitimacy - when there is a risk of embarrasment or reputation 4. Excitement - when an innovation depends on people being excited about it; social effervescence Each of these barriers requires social reinforcement to overcome. Knowing that other people have adopted an innovation makes the difference between *awareness* and *adoption*. Weak ties and strong ties have different network geometries. Weak ties look like fireworks, whereas strong ties look like fishing nets. Strong ties have a lot of social redundancy, and this makes people accountable, which fosters social cooperation and solidarity. ### Chapter 5 - Complex Contagion in Action: Memes, Bots, and Political Change In 2014, the Ice Bucket Challenge raised over $40milion for ALS. It was an example of complex contagion. Mathematicians actually predicted that the meme would take off, based on the network structure. That year, other computer scientists created bots to successfully spread some positive social memes. ### Chapter 6 - Contagion Infrastructure: The Importance of Wide Bridges # Quotes