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Title:Visualizing the Flow of Knowledge
Author(s):Dinh, Mai-Ly
Contributor(s):Jackson, Sally
Subject(s):Communication
Abstract:Within the field of computer-mediated communication, an increasingly popular domain for researching online social networks, visualizing citation linkages can help discover the most influential journal articles, most well connected author and emerging sub-groups of topics in the network. The present visualization chooses to examine paper citation and co-authorship patterns in Journal of Computer-Mediated Communication (JCMC) to recognize the substantial role the publication plays in adding network analysis to the communication literature. In fact, social and semantic network analysis enables communication scholars to understand how the adoption and use of new CMC systems impact social processes, specifically affordances and constraints of introducing new technologies to various contexts such as organizations and interpersonal relationships. Thus, understanding how knowledge flows, which authors have highest influence, and the various sub-specialties and sub-groups of authors emergent are essential to capture the evolution of the CMC field since 2005 as well as the frequency and impact of network analysis in the literature. The following visualization contains 459 articles and 17,909 nodes of works that are referenced between all articles and directed edges represent instances of citing. Software used are NodeXL, Gephi, and Sci2.
Issue Date:2015-04
Type:Text
Image
URI:http://hdl.handle.net/2142/74864
Rights Information:Copyright 2015 Mai-Ly Dinh
Date Available in IDEALS:2015-04-16


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