As a follow-up to my post about ten papers that shaped my science, here are ten favorite books. I limit myself to science-themed books; I get inspired by fiction /other non-fiction too. 🙂
Schelling, Micromotives and Macrobehavior, 1978
Many of my fellow computational social scientists have read it (and those who haven’t already, definitely should). This was probably the first book about social science I ever read. I did it as a Ph.D. student just after I started studying networks (recommended by Fredrik Liljeros). At the time, my main research topic was phase transitions in disordered superconductors. I loved the everyday problem solving it brought but loathed the fact that nobody around me seemed to care. Schelling’s book described, I thought, astonishingly similar types of modeling problems, and made me see a future ahead of both fun, abstract problems and conclusions I could share with others. PS: I also loved that all the examples come from the academic environment we know so well: the dying seminar series, why lecture halls fill up from the back, etc.
Watts, Everything is Obvious: Once You Know the Answer, 2011
I guess all academic fields have their vices. In theoretical physics (the area of my Ph.D.), it is the fetish for mathematical elegance that sometimes shrouds the common goals of explaining the world as we can measure it; in psychology, it might be a lack of reproducibly and the attitude to it. Everything is Obvious argues very convincingly that the social sciences are hampered by a compulsion to, even though common sense can be deceptive, use it to rationalize behavior. On the way to making this point, Watts’ book is an excellent exposé of many shapes of social science and a good intro for scientists who want to get a glimpse of the other side of the river. (Ah . . that was a reference to my alma mater Umeå University, whose campus is split by a river into social and natural science parts, not to Styx / Sanzu.)
Elster, Nuts, and Bolts for the Social Sciences, 1989
Now it will seem like I am contradicting myself, and maybe I am because Nuts and Bolts represents the kind of social science criticized by the previous item. I like Nuts and Bolts, though, because if you would explain social phenomena in words, what you really aim for is a narrative of connected mechanisms of individual behavior and decision making. These mechanisms need not be rational, although Elster is usually connected to rational choice theory, in the extended and revised Nuts and Bolts (called Explaining Social Mechanisms) he hints some skepticism of the explanatory power of rational choice theory. So it is really giving nuts and bolts, but for tips on the actual building process, we should listen to Watts.
Zemansky, Dittman, Heat and Thermodynamics, 1957
Thermodynamics is my favorite physics theory. Beautiful, accurate, self-contained, derived in a principled way, and complete (well, kind of). In comparison, statistical mechanics (that is closer to my research) is a hairy beast of semi-ill-motivated assumptions. Honestly, I like statistical mechanics too, but it is a much harder feeling to explain. It’s like my hometown—of course, I’m patriotic about it, but there is not a single objective argument for its greatness. Back to the book. The first lectures in my undergrad thermodynamics class were terrible, and the course literature some badly Xeroxed Swedish lecture notes. Ex mero motu, I bought Zemansky and Dittman’s book and read it during the lectures, aced the test, and liked thermodynamics ever since. I loved it to the point I made my own students in energy systems engineering overstudy the Rankin cycle.
Pisani, Wisdom of Whores, 2008
When my (then) student Luis Rocha and I studied the economics of Internet-mediated prostitution, this book was my first connection to a reality beyond the CSV files. The political conclusions of the book are probably a bit speculative, at least controversial. The greatness lies in the on-the-street descriptions. Without them, my own research would probably have lost track. Wisdom of Whores helped me to see the incredibly complex web of forces that are creating the economy of prostitution. There should be plenty of more to investigate for network scientists as it is a much more lateral, networky organization than other economies. But (alas!) we got no love in return as Pisani blogged the following:
Another thumbs down for the Swedish model. Not the leggy blonde, not even Sweden’s moralistic approach to the sex trade. This one is the Swedish research model, which has managed to turn the fascinating subject of on-line rating of hookers by Brazilian punters into something indescribably dull.
Pisani takes pride in calling herself nerd, but if she can’t see the point of detrended fluctuation analysis, is she really nerdy enough? 😛 Anyway, that was just fun. From our perspective—back then, I was at a physics department, and the phrase “data science” yet to be heard of in my world—we worried that it wasn’t severe enough.
Buckley, Harary, Distance in Graphs, 1990
This book is somewhat forgotten, but it was my introduction to the components of network theory—fundamental graph theory, centrality measures, etc. I guess I found it after first trying Bollobas’ Modern Graph Theory (that many early network physicists cited as a graph theory intro, although it is pretty heavy stuff . . ). I loved the style of Buckley and Harary, much lighter in tone than your usual textbook and funny at times (this is, after all, a book by the author of Is the null-graph a pointless concept?).
Kunen, Set Theory, 1980
There is something very uplifting about the foundations of mathematics. A beginner would think it (to be specific: Zermelo-Fraenkel set theory) is a tranquil thing at the base of all other science. But you might know the story—to get much of the mathematics we use every day, say the real numbers, we need to add the axiom of choice. But if we do, we get all kinds of bizarre paradoxes—like that you can divide a sphere into a finite number of pieces and reassemble it to two spheres of the same radii as the first. Doesn’t this prove that math is just as unruly as humans? In other words, we can read a textbook about set theory like great literature expounding the depths of human nature. Maybe that’s a bit too far, but Kunen’s book is readable and not the kind of math textbook that makes you feel like you’ve run into a wall at the first theorem.
Ambler, Adams, Gould, Spatial Organization, 1971
My father (architect) had this as a textbook for some course in urban planning. It was always sitting on a shelf in my parents’ house, and it didn’t interest me until just half a decade ago. But, to my astonishment, it has so many ideas that currently float around in the network / comp-soc-sci / urban informatics communities. The optimal windowing of temporal networks to mention just one example:
. . and finally, two books much further from my research topics . .
McMahon, Understanding Language Change, 1994
Everyone has their own X in “X is the archetype of a complex system.” My X is language. Although I never had a serious research project about it, it is always on the upper half of my todo list—but there would still be some platinum-card project stepping into the line ahead. The closest I got to starting a project was perhaps to read this book. It showed me a wonderful world of old-school acquired knowledge gleaned from obscure libraries and ancient fieldwork, but also opening up for data science and modeling from evolutionary biology.
Lévi-Strauss, Tristes Tropiques, 1955
Essentially this is an autobiography by the famous French anthropologist Claude Lévi-Strauss. But it often spirals out of the memorial realm, into general philosophizing about the role of anthropology, science, cultural clashes, and intellectual endeavor in general. It is much more than an anthropology book. My mind reading it was more tuned to some philosophy or fiction mode. Tristes Tropiques could be read at different levels, and the storylines pieced together in many ways—as such, it succeeds where many other books have failed terribly (but I guess I should save posts about bad books to when I’m really grumpy and really old).