The article advances a new way to think about computational research, in general, and computational communication research, in particular. Contrary to current definitions of “computational science,” which emphasizes its inductive nature, we define computational research as an incomplete inductive process, blending both theoretical and data-driven methods of discovery. Communication theory needs to be driven by a clear concept of human needs and abilities, recovering and extending known theoretical insights from mass and interpersonal communication research. The definition we propose for computational communication research has a practical implication. Relying on theory, the definition demands to identify specific processes and domains within the field of computational communication research. The processes include communication production, behavior, and effects. The domains include collaboration, trust, and data storytelling and journalism, while the methods include content and network analyses. The article starts with a broad definition of the “computational” approach, using the Johari window. We continue with a typology of computational communication research, which blends reviews of foundational texts with summaries of leading research. In the conclusions, we discuss the strengths and identify new opportunities in the field of computational communication research. This article is categorized under: Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction Commercial, Legal, and Ethical Issues > Social Considerations Fundamental Concepts of Data and Knowledge > Big Data Mining.
|Journal||Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery|
|State||Published - Jul 1 2019|
- computational science
- research methods