The “Social” Side of Big Data: Teaching BD Analytics to Political Science Students

In an increasingly technology-dependent world, it is not surprising that STEM (Science, Technology, Engineering and Mathematics) graduates are in high demand. This state of affairs, however, has made the public overlook that not only computing and artificial intelligence are naturally interdisciplinary, but that a huge portion of generated data comes from human-computer interactions, thus they are social in character and nature. Social sciences practitioners should hence be in demand too, but this does not seem the case. One of the reasons for such a situation is that political and social science departments worldwide tend to remain in their “comfort zone” and see their disciplines quite traditionally, but by doing so they cut themselves out of many positions today. The authors believe that these conditions should and could be changed and thus in a few years created a specifically tailored course for students in Political Science. This paper examines the experience of the last year of such a program, which, after several tweaks and adjustments, is now fully operational. The results and students’ appreciation are quite remarkable. Hence the authors thought the experience was worth sharing, so that colleagues in social and political science departments may feel encouraged to follow and replicate such example.