Three Hard Questions about Network Science
I just returned from a nice junket to beautiful (at least in the fall…) Maine where I gave talks at Bowdoin College and University of Maine. Both institutions were impressive for different reasons, and I met a lot of fun people. The Q&A periods of the talks highlighted three important and hard questions about network science that I think all of us should thinking about how to answer.
A first caveat is that these three questions are interrelated and at times there will be overlap in this write-up. A second caveat is that I will be answering these mostly from the perspective of environmental policy, policy science, political science, and social science more broadly. But the questions apply equally to the physical and biological sciences, and I will be forwarding this blog around in an effort to start a dialog. Who knows, there might be a collaborative paper in this somewhere. A third caveat is that this blog is going to be long—sorry. Bottom-line, for those who trust me and don’t want to read anymore: Network science is a real science that is useful to society and can answer core questions about social systems and behavior.
Why is network science useful?
To answer this question, first we have to decide what “useful” means. Network science can be useful for answering basic research questions in social science, and is also for basic research questions about networks as a unique field of inquiry (see next section). I think it is easy to make the case that network science is useful for pursuing basic understanding of intellectual research questions.
But when I was asked this question at Bowdoin, I really think the person was asking about the applied or public usefulness of network science. A colleague at Maine suggested that the media and public rely on two “frames” for translating science, the “oh wow that’s cool” frame and the “this will make society better off frame”. Networks have done pretty good with the “oh wow” frame with work like Fowler and Christakis suggesting that your friends make you fat, and things like “small world” networks that seem to explain why you end knowing people in random places (at least that is how the public thinks about it).
The “better off” frame is maybe a little harder although other network scientists might disagree. But here are a few potential “better off” factoids, which I could dig up citations for if I have time but I won’t have time so I won’t do it! So call the following my “best professional judgment” about some uses of networks science for social behavior:
•Identifying central individuals and brokers who can help spread ideas and behaviors.
•Identifying disconnected individuals who need to be brought into social communities.
•Identifying key social relationships that should be established in order to integrate diverse communities.
•Restructure organizations enhance economic performance.
•Develop best practices for leveraging social influence to improve human health and welfare, including avoiding disease.
•Early warning systems for disease outbreak and other good or bad contagion processes.
•Identifying bad guys—whether you think the security agencies are the evil empire or American heroes, they have used network tools to achieve national security goals. I don’t have to make any moral judgments about the tool users to make a claim that the tool has some usefulness.
•Intervening in governance systems and policies in order to make them more effective at solving social problems, or achieving other normative goals like democracy, fairness etc. This includes providing policy-makers with network-smart best practices(self-promotion: this is where my work is focused, and I still think we have a long way to go here).
•Provide indicators for empirical measurement of the effectiveness of policies and social programs that aim to build communities of various types.
•Identifying disconnected individuals who need to be brought into social communities.
•Identifying key social relationships that should be established in order to integrate diverse communities.
•Restructure organizations enhance economic performance.
•Develop best practices for leveraging social influence to improve human health and welfare, including avoiding disease.
•Early warning systems for disease outbreak and other good or bad contagion processes.
•Identifying bad guys—whether you think the security agencies are the evil empire or American heroes, they have used network tools to achieve national security goals. I don’t have to make any moral judgments about the tool users to make a claim that the tool has some usefulness.
•Intervening in governance systems and policies in order to make them more effective at solving social problems, or achieving other normative goals like democracy, fairness etc. This includes providing policy-makers with network-smart best practices(self-promotion: this is where my work is focused, and I still think we have a long way to go here).
•Provide indicators for empirical measurement of the effectiveness of policies and social programs that aim to build communities of various types.
I’m sure my social science colleagues will greatly expand this list, and the bio-physical scientists will only add their own big list.
Is network science a real“science”?
To answer this question, first we have to decide what “science” is. I refer you to Thomas Kuhn , Karl Popper, and the field of epistemology for real answers; for now I will give my own hack definition. A “science” or scientific discipline is a collection of core research questions, competing theoretical frameworks/hypotheses, and methodological approaches. Of course these things are always in flux but among any community of scientists there some core set of questions, theories, and methods that most people will recognize. Once there the communities and associated knowledge has coalesced enough, a scientific discipline will acquire its own set of institutional arrangements: professional societies, journals, conferences, listservers, Facebook pages, Twitter handles, academic departments, and funding sources.
I definitely think this type of convergence is happening for network science and therefore it qualifies as a very young scientific discipline with the potential to emerge into an enduring scientific discipline. Just a decade ago, the study of networks remained fragmented across many different disciplines including sociology, political science, economics, physics, mathematics, and computer science among others. Now the people in those disciplines who work on networks are in frequent communication. Core questions about the structure and function of networks are beginning to emerge. Methodological and theoretical approaches are cross-fertilizing. It is happening very fast too—so fast I wonder if any other science has witnessed such a rapid evolution. There is a new journal called Network Science, the term is being used by most people, and it has many of the other institutional accoutrements of a scientific discipline.
Where is the political science (insert your home discipline here) in network science?
When I gave my presentations at Maine, one of the political scientists in the audience had a hard time recognizing the political questions embedded in the work. Of course I thought the political science was obvious, because the work focuses on public policy, governance of collective action problems, and involves lots of different Federal, state, and local bureaucracies, interest groups etc. In her presidential address to the American Political Science Association, Lin Ostrom wrote that collective-action and institutions are the core question of the discipline and of course I agree (Jane Mansbridge’s 2013 APSA presidential address reiterated this point).
But some of the more traditional disciplinary political scientists only recognize their discipline when they hear words like “presidents”, “courts”, “elections”, “voting” etc. All disciplines have their purists (probably necessary from an epistemology standpoint but it sure is annoying…) and therefore it is the responsibility of people working in an interdisciplinary area like network science to demonstrate its usefulness to political science. We have to make it explicit and obvious, and it would be naïve for us to expect the disciplinary purists to make the realization on their own. They are the status quo and have no incentive to change their views. So as a sub-community within the discipline, the political scientists who work on networks have to continue to press the case, or network science may be viewed as another fad. I think this would be really sad (rhyme..nice), because in my opinion networks are enduring features of social systems and we are missing a huge part of the story if we don’t study them.
A related issue was recently brought up by John Padgett (U of Chicago) at the 2013 business meeting of the political networks section in APSA. Padgett, who is famous for his analysis of social networks in Renaissance Italy, hypothesized that much of the discipline viewed political networks as a “method” or “technique”, rather than a fundamental scientific approach that could crack open core questions in political science. I believe this image needs to change, and again it is the responsibility of network scientists to do it.
Note there is an uneasy tension here between network science as a separate discipline, versus an approach that is applied to political science questions. As a stand-alone discipline, network science needs to have its own core questions, theories and methods; these can easily exist (and already do) without ever mentioning the word politics. Call this basic research if you want. But when these ideas are “applied” to political science, then it becomes harder to claim that network science is a stand-alone discipline rather than just a branch of political science.
Well I’ve written something that epistemologists and logicians would probably nail me for. But I think these three questions are important. If you don’t like my answers, write your own, or let’s try to figure out as a community how to answer them.
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