Six Degrees: The Science of a Connected Age (Open Market Edition) [Englisch] [Taschenbuch]

Contrary to some recent remarks from an apparently aggrieved reader, I think Six Degrees is actually quite different from most books claiming to cover new and exciting scientific developments. Far from being self-aggrandizing, I found it's tone remarkably humble and generous to others. Watts, in fact, is the first person to call his subject the "new" science of networks, and goes to considerable lengths to acknowledge, even glorify, his intellectual predecessors. He doesn't mention every scientist who has made contributions: it's not meant to be a text book, thankfully.

Watts also has bigger fish to fry than simply the importance of networks in everything under the sun. His real message is that social reality has to be understood both in terms of the way people are connected and also the way they behave. So focusing on individual behavior to the exclusion of their interactions misses half the story, but so does just focusing on the interactions (as much of network theory has done). It's true that many of the ideas are quite old (and Watts again is the first to point this out), but the way they are put together is new, and that is what is so interesting about it.

The results are often quite deep and thought provoking, which means you have to actually read the book to understand what's in it, but Watts always comes up with an entertaining anecdote or analogy to make even the hardest concepts palatable and interesting. Overall, it's a great, fun read about a fascinating subject that really makes you think. And what more can you ask from a book?

I've always been fascinated by social networks, having read Granovetter's work on strong vs. weak ties. As a career coach, I naturally talk to clients about the joys and frustrations of networking -- and I loved the movie "Six degrees of separation."

If you're looking for an easy piece of entertainment, this is not the book for you. Watts shows how this field has advanced by combining research efforts in information science, physics, mathematics and sociology. We look over his shoulder as he collaborates with other scientists to solve tough problems -- and get a glimpse of modern science in action (although I think Watts emphasizes the more positive, cooperative aspects of "doing science").

Students of psychology will enjoy his discussion of Milgram's famous experiment -- messages mailed to a Boston stockbroker -- and the real, as compared to legendary, results. Milgram's even more outrageous obedience experiment, which Watts includes, also deserves a footnote: subjects refused to obey (a) when the experimenter broke the rules and gave reasons for the order and (b) when they were able to reconstruct their roles outside the laboratory.

I began by borrowing this book from a library but realized that it needs to be owned. It's not a quick, one-time read. Although it's accessible, you have to pay attention and I found a need to read sequentially, from chapter to chapter. But if you read carefully, you'll change the way you look at the world.

As other reviewers have noted, Watts shows how daily life is influenced by properties of networks: Why do some viruses, computer and biological, spread, and why others come to a quick halt? Why do airline hub-and-spoke networks often break down? How do computer searches work and what makes them effective?

We're living in an increasingly connected world and this book will help us see and understand the connections more clearly. I think it's a must for anyone who wants to comprehend our world today.

I wrote this book review as an assignment for a class. Its intended audience was sociologists unfamiliar with network theory. The intended audience for the book though is much wider. If you want the math, read academic journals.

In the first chapter of Six Degrees Duncan Watts notes that gossip, power outages, epidemics, even properties of the human brain such as consciousness are phenomena that may be understood as emerging from the interaction of their constituent elements. Through such examples, he calls attention to the broad applicability of his subject matter. Having provided this motivation, Watts spends much of first half of the book discussing what he knows best, "small world" networks. In the second half he presents a network perspective for a wide range of topics such as epidemics, externalities, speculation, social decision making, and organizations.

Like many academics marketing books to non-academics, Watts skillfully weaves his personal story with the science. His personal story is not only provided to keep laymen interested. Watts is now a member of the sociology department at Columbia University, but one can't help but wonder whether he identifies as a sociologist? How would other members of the discipline respond to a youngster whose PhD is in theoretical and applied mechanics who may never have read Durkheim? His early collaborators were mathematicians, physicists, and computer scientists lodged in appropriate departments. Watts though, has become a strong proponent of interdisciplinary science, and he respectfully acknowledges research that has been done in anthropology, sociology, psychology and economics.

His first foray in the social sciences was inspired by the "small world" phenomenon. When two people are surprised to learn they have mutual acquaintances, someone often says, "It's a small world." In 1967, social psychologist Stanley Milgram decided to investigate how small the world really is. He tasked randomly selected residents of Boston and Omaha with getting a letter to a stockbroker who lived in Massachusetts. The rule was, they could only send the letter to people they knew on a first name basis. Amazingly, the letters that reached their destination usually did it in just 6 steps. This finding was then misconstrued and became the urban legend that there are six degrees of separation between any two people. Despite the widespread interest in the small world phenomena, little progress was made understanding it over the next thirty years.

Watts got interested in this problem when he was a graduate student in theoretical and applied mechanics. He and his advisor, Steven Strogatz, had been trying to understand how crickets' chirping becomes synchronized without a conductor cricket. Watts surmised that the timing of a cricket's chirp must be influenced by where it is located and the other crickets it is listening to. The ability to synchronize may depend on the structure of this network of crickets. The relationship between network structure and network phenomena such as synchronicity suddenly seemed broadly important, and he was surprised to learn how little mathematical attention it had garnered. Recalling the idea of "six degrees of separation," Watts and Strogatz turned to social networks and set about building simple models. Where Milgram had asked, "How small is the world?" they were now asking, "What does it take to make a world small?" This reframing of the problem was fundamental to the contribution they were to make.

Watts and Strogatz settled on modeling just two facets of social networks. One was the "small world" aspect, quantified as average path length (the number of links required to connect two randomly chosen people). The second was clustering, the extent to which my friends overlap with my friends' friends. What makes small world networks surprising is that short path lengths and high clustering are inherently antagonistic. Paul Erd?s and Alfred R?nyi rigorously proved that path lengths are short in networks with no inclination towards increased clustering, a random graph in the parlance of mathematicians. At the opposite extreme, if everyone was friends with all of their friends' friends, short path lengths would be impossible (in fact social groups would be completely disconnected from each other). After countless computer simulations, Watts had two important results. The alpha model captured the small world balance of path length and clustering. The beta model showed that if a network was systematically clustered, to the point of fragmentation, just adding five random links (edges) halves the average path length. He then began acquiring and examining network data sets. Remarkably, Hollywood actor collaborations, the neurology of C. Elegans, the power grid of the Western United States, interlocking boards of directors and the world wide web are all small world networks.

Next Watts reviews the work by L?zl? Barab?si, a physicist at the University of Notre Dame. His major contribution is research on scale free networks. Sociologists have long been concerned with questions surrounding the number of connections (degree) people have. Barab?si realized the importance of the degree distribution in a network. The degree distribution of many networks is approximately Poisson but Barabasi showed that the degree distribution of other important networks follows the highly skewed power-law. The distribution of wealth and the size of cities both fit this model. Furthermore he showed that this distribution will follow if the future growth rate is linearly related to the present size. This has obvious implications for these two examples and calls to mind Merton's Matthew Effect.

Barab?si's book, Linked, is similar to Six Degrees in that is geared to the general public and reviews many of the most important advances in network scholarship. Do Watts and Barab?si overstate their case? Rather than get bogged down in the semantic debate that is likely to arise from the claim to a "new" science, we should appraise the value of this line of research. It clearly has potential but Watts himself sometimes alludes to the difficulties in achieving that potential. Watts' work is mostly theoretical. Six Degrees offers a thought provoking network perspective on many topics but little help harnessing the theory in empirical work. Appropriate data may be hard to come by. Perhaps Watts has provided ideas that creative empiricists will find ways to exploit, but there are methodological challenges that may prove to be stubborn.

Despite some important exceptions such as Granovetter's Strength of Weak Ties sociologists have tended to take one of two approaches. One was to focus on the relationship between social structure and network structure. The other was to view network ties as sources of information or influence. This means exploring the association between position in a network, and a node's identity or power. Watts is right to call attention to the fact that these approaches usually ignored dynamics: changes in the network structure (changes in network connections), and what individuals do on the network (search for information, spread rumors, make decisions). Network data that captures these dynamics may be harder to come by.

Furthermore, large detailed datasets may be limited by the computational power available. Even simple computer simulations can be very computationally demanding. Threshold models of decision making, discontinuous phase transitions and cascades - many of the fundamental concepts in the study of networks are nonlinear. Proving the existence of causal relationships is always a challenge but these complex systems make a hash of everything. The measured effect of an independent variable, on average or at the margin, tells us little about the importance of that variable.

Despite a reasonable display of humility and respect, Watts should be criticized for the sociology he leaves out. Neither space limitations, nor a rush to publication can justify the gaps in his otherwise helpful recommendations for further reading. For example, Blau, Burt, Coleman, Homans, Laumann, Marwell and Oliver are conspicuously absent from the list. Perhaps this observation should not be overanalyzed but it does brings us back to how Watts will be received by sociologists and what impact he and scholars outside the discipline will have on sociology. It is hard for this reviewer to understand how anyone who reads this book could come away uncertain of the value of mathematics for theory development as well as empirical analysis. Model building can simplify and clarify, enhancing our intuition. Watts would never argue that all sociologists should drop what they're doing and begin running computer simulations, just that we should be open to such approaches. As he points out, "For any complex system, there are many simple models we can invent to understand its behavior. The trick is to pick the right one. And that requires us to think carefully, to know something about the essence of the real thing." Sociologists know something about the real thing. That's why we can't leave all the modeling to physicists and economists.