START’s graduate program is launching a new course, Special Topics in Terrorism Studies: Social Research Methods and Socioinformatics, taught by ICONS Director Dr. Bob Lamb. The course introduces research methods for studying complex problems in extremism, security, and human well-being, with a focus on the enabling conditions for extremism. In the Q&A, Dr. Lamb explains why he developed the course and what competencies and deliverables students can expect by the end of the semester.
What need or gap does the course address within terrorism studies and social research methods?
Other courses teach students statistics, case studies, econometrics, maybe even wargaming or machine learning techniques. These are all valuable and entirely appropriate for many of the problems students will encounter in their careers, and it’s certainly valuable for them to be literate in the standard methods used in policy circles.
But some problems are more complex than what some of these methods are designed for. I once saw an otherwise serious policy scholar calculate correlation coefficients on country-year data to find patterns about conflict and fragility, which are notoriously complex problems. During my career, I’ve read countless other papers and policy reports whose “Background” section acknowledges the problem’s fundamental complexity but whose “Methods” section says, in effect, “but we’re going to use linear regression anyway,” because that is the method they were taught in graduate school. And I absolutely do think that should be taught in graduate school.
There are, however, scores of other methods that have been explicitly designed for the study of complex problems. By complex I mean: a lot of things interact in a lot of ways that make it at best unintuitive (and at worst impossible) to predict how trying to change some things will affect the outcomes we ultimately care about. Humans have come up with a lot of different ways to account for those interactions and outcomes, including participatory approaches (group model building, role-play), visual mapping, qualitative and quantitative modeling, computational simulation, machine learning, and more.
This course is going to introduce students to these unconventional methods, with a focus on learning methods they can start applying right away (participatory elicitation, system mapping, etc.) and literacy that will enable them to engage constructively with research or experts using specialized methods (system dynamics, social network analysis, agent-based modeling, etc.).
What core ideas about complexity and systems thinking guide the course, and how do they affect how students choose research methods?
The core idea is that problems exist on a spectrum from fairly straightforward to extremely complex, and the tools and approaches available for solving those problems can also range from very simple to very sophisticated. I call this “systemic depth”: more complexity, more systemic depth. And just like you can’t dig a deep hole with a short shovel, you can’t solve deep problems with shallow tools. Policy institutions need to be able to mobilize complexity if they want to have even a hope of solving a complex problem.
So what does that mean in practice? We need to be able to understand the dynamics of the problem (how it changes over time) and the structure of the problem (how the things driving those changes interact), so we can know if any proposed solution is rich enough to deal with all the ways the problem might respond to it. If it’s a simple capacity problem, then “doing more” is the solution, like hiring more social workers. If it’s a problem that touches on incentives people can adapt to, then maybe “doing less” is the right move, like how closing streets can improve traffic flow. If it’s a problem that touches on identity or false beliefs, or involves people capable of adapting to the solution, then “different institutions doing different things in particular sequences” might be the only thing that could work. Like if you want to reduce the total number of trafficking victims over time, you can’t just rescue victims without also degrading the perpetrators’ recruitment capacity.
Students will be introduced to different methods capable of identifying the kinds of dynamics and structures that drive systemic depth: looking for feedback loops, tipping points, second-order or cascading effects, state variables, rates of change, identity and belief as drivers, and so on. Then they’ll apply them to real-world problems related to extremism.
How do you teach and assess multi-method research design while keeping the course cohesive?
All students will be working on some aspect of extremism as a topic, so there will be a common research domain. We’ll touch on recruitment and radicalization processes, distinguishing, for example, between linear vs. emergent process, but we’ll spend a lot of time on the enabling conditions that make it so hard to predict and prevent: social identity, polarization, echo chambers, algorithmic manipulation, disinformation, dehumanization, norm diffusion, narrative resonance, the role of AI agents, and so on. Each of these has its own nonlinear or dynamics, and some are notoriously hard to measure. But we’ll compare studies that use different methods on the same topics to see how each approach can illuminate a different dimension and determine whether new insights can emerge from the combination.
This is a key reason the course focuses on the use of informatics tools, which help with translating concepts across different domains or disciplines, connecting data and modeling paradigms, and connecting insights that wouldn’t otherwise be possible. Informatics approaches have made fields such as genomics and climate science possible, and I want students to learn how to improve social research around real-world complex problems such as those that make extremism possible.
By the end of the semester, what outcomes should students be able to demonstrate, and who is this course a best fit for?
I want students to be able to diagnose the systemic depth of a social or extremism-related problem and match method choices to that depth. I want them to be competent in the application of at least two or three method families (e.g., combining ethnography or participatory methods with network mapping) and familiar with the rest. They should leave the course with the capacity to articulate how similar concepts (“institution”, “legitimacy”) might mean different things to different audiences and to connect and translate those meanings across methodological paradigms and communities. They’ll be aware of how the structure and culture of policy institutions affects their ability to implement effective solutions. And they’ll have ethical fluency around issues such as epistemic pluralism (different ways for knowledge to be valid), collective benefit, privacy, transparency, and non-extractive community engagement.
The course is perfect for anyone moving into a field where the problems either are already acknowledged as being complex or are getting worse, cycling between better and worse, changing qualitatively over time, or simply not getting better despite decades of effort and millions or billions of dollars in investment. Complexity is what makes terrorism and extremism so hard to address, of course, but also climate inaction, democratic erosion, global realignment, human trafficking, crime, housing, conflict, disinformation, and many others topics. So while it’s part of the terrorism studies minor, it’s a radically multidisciplinary course that would be appropriate for students in any discipline whose difficulties involve human beings.