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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Wiley Interdisciplin...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Article . 2019 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
DBLP
Article . 2019
Data sources: DBLP
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Computational communication research

Authors: Sorin Adam Matei; Kerk F. Kee;

Computational communication research

Abstract

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 InteractionCommercial, Legal, and Ethical Issues > Social ConsiderationsFundamental Concepts of Data and Knowledge > Big Data Mining

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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