Book
By Damon Centola
1
How did movements like the Arab Spring and Black Lives Matter take off when they did? How did Lord Kitchener recruit 2,000,000 volunteers at the start of World War I? Why did Twitter take hold while Google+ has failed? What surprising lessons can we learn from Covid 19? From the spread of Covid-19 to the rise of political polarization, from implicit bias to genetically modified food, from NASA to Netflix - it's time to think differently about how change works. Professor Damon Centola is the world expert in the new science of networks. His ground-breaking research across areas as disparate as voting, health, technology and finance has highlighted powerful and highly effective new ways to ensure lasting change. In this book, Centola distils over a decade of deep experience into a fascinating new theory that challenges previous assumptions that new ideas are either contagious or not. Change shows that beliefs and behaviours are not transmitted from person to person in the simple way that a virus is. The real story of social change is more complex and much more interesting. When we are exposed to a new idea, our social networks guide our responses in striking and surprising ways. Drawing on deep-yet-accessible research and fascinating examples, Change presents a paradigm-shifting new science for understanding what drives change, recognising our blind spots and how we can change the world around us.About the AuthorProfessor Damon Centola is Director of the Network Dynamics Group at the University of Pennsylvania. He was previously at Harvard and MIT. His work has been published across several disciplines in the world's leading journals, including Science, The Proceedings of the National Academy of Sciences, Nature Human Behavior, The American Journal of Sociology, and Journal of Statistical Physics.His speaking and consulting clients include Amazon, Microsoft, Apple, Cigna, the Smithsonian, the American Heart Association, the National Academies, the U.S. Army and the NBA. Popular accounts of Damon's work have appeared in the New York Times, Washington Post, CNN, Wall Street Journal, Wired, TIME, The Atlantic, and Scientific American.