Sunbelt XXXI International Network for Social Network ... - INSNA
Sunbelt XXXI International Network for Social Network ... - INSNA
Sunbelt XXXI International Network for Social Network ... - INSNA
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A Proposal For A <strong>Network</strong> Science Revolution Through Angle Measurement And VisualizationMartinez‐Garcia, Orlando I.VisualizationMeasures, <strong>Network</strong> Dynamics, Triads, Geometry, <strong>Network</strong> Visualization, Dyadic AnalysisWED.PM2Classical <strong>Network</strong> Analysis methodology has focused on mapping nodal and directed or undirected edge relations of power based on their size, <strong>for</strong>m, length,color and closeness. However, I have noticed a common omission that has been generalized within the field of network science: the measurement of anglesand their visual representation as they evolve from single nodes to dyads and triads as basic kernels <strong>for</strong> larger networks triadic dynamics as networks getlarger. The existing literature exploits triads focusing on the role of the node and giving weight to the edges without using an elemental geometric principle,angle measurement. In that process, network graphs loose a spatial‐time sequence dimension that triadic relations represented through their anglemeasurement based on power or strength of things being measured would generate through different triangles that entangled together, would produce morerigorous, faithful and holistic structural models and maps. I will develop perspectives on why angle measurement is a better tool <strong>for</strong> multidimensionalweighted relationship graph and why angle measurement in triads would be revolutionary in network topology and visualization.A Revisited <strong>Social</strong> <strong>Network</strong> Analysis Using Author Co‐citation DataKim, HyunjungKnowledge <strong>Network</strong>sCitation <strong>Network</strong>s, <strong>Social</strong> <strong>Network</strong> Analysis, Citation AnalysisTHURS.AM2This study will be an extension of a previous research on author co‐citation using social network analysis. The research examined the social network of scholarsin the field of Communication by analyzing author co‐citation patterns. A matrix containing the number of documents cited by pairs of authors is used <strong>for</strong> socialnetwork analysis of scholars on the editorial board of Journal of Communication, one of the journals published by the <strong>International</strong> Communication Association(ICA). Author co‐citation data is retrieved from <strong>Social</strong> Science Citation Index (SSCI) and UCInet is used to analyze the data and to create a network map of thescholars, which helps to visualize the knowledge structure of the communication field by identifying groups of authors who are more central than others. Inaddition, the research tries to find out if there are any factors, such as author’s educational background, current affiliation, or subject specialty, influencing theknowledge structure. The previous study used author co‐citation data collected until 2008, so this study will be used to compare the current author co‐citationpattern with data from the previous research to see if there’s any change over time.