Computational Communication Science| Computational Communication Science: A Methodological Catalyzer for a Maturing Discipline

Martin Hilbert, George Barnett, Joshua Blumenstock, Noshir Contractor, Jana Diesner, Seth Frey, Sandra González-Bailón, PJ Lamberson, Jennifer Pan, Tai-Quan Peng, Cuihua (Cindy) Shen, Paul E. Smaldino, Wouter van Atteveldt, Annie Waldherr, Jingwen Zhang, Jonathan J. H. Zhu


This article reviews the opportunities and challenges for computational research methods in the field of communication. Among the social sciences, communication stands out as a discipline with a relatively low-profile institutionalized focus on the in-house development of methods. Computational tools are changing this, and they are catalyzing a new set of methods directly suited to tackling foundational research questions in communication. We systematically review how computational methods affect the three fundamental pillars of the scientific method: observational approaches (i.e., digital trace data), theoretical approaches (i.e., computer simulations), and experimental research (i.e., virtual labs and field experiments). We stress that data are a catalyzer but not a requirement for computational science. We explore how observational, theoretical, and experimental approaches can be combined and cross-fertilize one another. We conclude that taking advantage of computational methods will require a systematic effort in our discipline to develop and adjust these methods.


computational science, research methods, big data, simulations, online experiments, methodology.

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