Computational Communication Research

Aims & Scope

CCR publishes articles that further the understanding, development and application of computational methods in communication research. Computational methods include (but are not limited to) methods such as text analysis, social/semantic network analysis, online experiments, machine learning, visual analysis and agent-based modeling and simulations. Computational methods can be applied to “big data” and social media or (online) behavior data, but can also be used to provide a more sophisticated understanding of “small data” or for theoretical explorations. Submissions should discuss, introduce, or apply computational methods to build and/or test theory or to quantify, analyze, explore or visualize communication structures and processes. In particular, we welcome submissions that : Apply computational methods to communication research questions; Present innovative computational methods for communication research; Evaluate or validate computational approaches to communication research; Address the role of computational methods in communication research; Present or validate tools, software packages, and datasets that are useful for communication research.

A twelfth criterion — whether APC fees are clearly disclosed — is not scored here; it is left out of the total rather than counted as a failure. Publication charges appear in the metrics card above.

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification