Students and Cutting-Edge Research
2 March 2016 - By Damian Trilling, assistant professor Political Communication & Journalism: 'I think that as academics we should strive to shape the future of our field, rather than just reproduce old recipes.'
It's seven o'clock in the morning and I'm sitting in the intercity train from Amsterdam to Berlin, where I have to give a talk about automated content analysis. Coincidentally, yesterday, I did not only prepare the talk (yes, not only students do things last minute), but I also worked on some details of the Research Master course Big Data and Automated Content Analysis, which starts in a few weeks.
This made me think about how closely related our research and teaching often are, and how cutting-edge some of the stuff we teach actually is - or at the very least should be. We sometimes tend to forget this. Of course, some basics remain the same for a long period of time, and also, there are many things where we actually lag behind (Google can make better predictive models of internet use than I). But in general, I think that as academics we should strive to shape the future of our field, rather than just reproduce old recipes. And that's were both my talk in Berlin and the course I'm teaching come together.
I have been invited to Berlin to tell how to conduct content analysis on a larger scale than typically done (and taught) in our field, using things like virtual machines, cloud computing, and large-scale databases – things that many internet services rely on as well. Interesting for research, one might say, but where does teaching come into play? As it turns out, a lot of the things in my talk have been put into practice by our students. Joanna, for instance, has contributed a lot of code to identify important pieces of information on a variety of Dutch news sites, and Arno is working on a web interface to the data. But of course, they did not start from scratch: one and two years earlier, Petro and Theresa had made a start. And Erik and Tanushree are now contributing their knowledge to a project at the Political Science department.
Working on such computational social science projects, thus, is a lot of giving and taking. When I write a piece of code (because the software to do a particular analysis does not exist yet) and a student can use it for his or her thesis: sure, go ahead and use it. But this also means that if you improve this code, you have to share it with the rest of us. And yes, you can use my data. But when you collect additional data, contribute it back. That's how science moves forward. And it is also what makes teaching in this area so fascinating: we teach the basics and some cutting-edge stuff, but if you want to move on (to get your research participation points, to write a thesis, or as a paid student assistant), you can actually contribute to something that did not exist before.
And that seems to be interesting enough to have other universities pay your train tickets and hotel expenses, because they want to learn about it.
Dr Damian Trilling (32) is assistant professor Political Communication & Journalism. He completed a ‘Magister’ degree in Communion Science with minors in Dutch studies and German linguistics at the University of Münster in 2009. He obtained his PhD in Communication Science at the UvA in 2013.