Masters Thesis
The Nature of Networks: A Structural Census of Degree Centrality across Multiple Network Sizes and Edge Densities (Fall, 2007)
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This thesis examines the mathematical properties of networks, specifically degree centrality at the actor (node) and group (network) level. An algorithm is presented for the creation of all possible edge, node, chain and group degree structures for a given network size and edge density. The census of networks size five through fifteen are used to investigate degree distributions, degrees of freedom and effects of size and density on actor and group degree. Variability (entropy) of information based on actor and network degree centrality structure variations are provided as insight into the complexity of networks. Results indicate an underlying structural influence irrelevant of context suggesting residual data as the contextual behavior element. Power law, fat tail and low density distributions are empirically produced through non-contextual network census suggesting the current behavioral models as structural influence rather than human influence. Finally a general theory for autonomic structural influence is presented with implications for past, present and future research in the area.
SunBelt Conference Papers
The Nature of Networks: A Structural Census of Degree Centrality Across Multiple Network Sizes and Edge Densities (2008)
This paper examines the mathematical properties of networks, specifically degree centrality at the actor (node) and group (network) level. An algorithm is presented for the creation of all possible edge, node, chain and group degree structures for a given network size and edge density. The census of networks size five through fifteen are used to investigate degree distributions, degrees of freedom and effects of size and density on actor and group degree. Variability (entropy) of information based on actor and network degree centrality structure variations are provided as insight into the complexity of networks. The results indicate an underlying autonomic structural influence irrelevant of context suggesting residual data as the contextual behavior element. Power law, fat tail and low density distributions are empirically produced through non-contextual network census suggesting the current behavioral models as structural influence rather than human influence. Finally, a general theory for autonomic structural influence is presented with implications for past, present and future research in this area.
Jacob's Ladder 11.0 and Information Saturation ABM 1.0 (2008)
This presentation demonstrates two new software packages, Jacob‘s Ladder 11.0© and ABM. Jacob‘s Ladder 11.0© is software for the visualization, intonation and animation of network data in a virtual reality (VR) space. Jacob‘s Ladder 11.0© is targeted toward individuals interested in the examination of social networks and or any research involving the use of multidimensional data matrices. The software provides individuals with the ability to animate and/or overlay real-time data of any type or size in a VR space with maximum variability in dimensional representations including, but not limited to, object size, type, position, color, transparency, temporal positioning and audio frequency. This paper demonstrates Jacob‘s Ladder 11.0© with data describing the migration among Canadian provinces. The results are presented along with implications and future directions for this software. Agent based modeling (ABM) is rapidly becoming a common methodology for analyzing and understanding the underlying process of social behavior. Network evolution and dynamics are two of its applications (Monge & Contractor, 2003). This presentation introduces ABM software created to understand information diffusion among network connections based on weighted probabilities of communication likelihood, message type and age of message. The software provides users with the ability to designate the originators of messages. Results include two visual representations of the model in action to determine message saturation percentage and time to saturation.
Jacob's Ladder 11 - Multidimensional Data Animation, Visualization and Intonation Application for Creating Virtual Reality Displays (2006)
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This paper introduces Jacob's Ladder 11.0©, software for the visualization, intonation and animation of multidimensional data in a virtual reality (VR) space. Jacob's Ladder 11.0© is targeted toward individuals interested in the examination of social networks and attitude relationships or any research involving the use of multidimensional data matrices. The software provides individuals with the ability to animate and/or overlay real-time multidimensional data of any type or size in a VR space with maximum variability in dimensional representations including, but not limited to, object size, type, position, color, transparency, temporal positioning and audio frequency. This paper then demonstrates Jacob's Ladder 11.0© data describing the migration among Canadian provinces. Results are presented along with implications and future directions for this software development.
