ISBN: 9781156606797

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters:… Más…

Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Social Weather Stations, Sexual Dimorphism Measures, Dynamic Network Analysis, Social Statistics, Network Probability Matrix, Social Network Change Detection, Economic Statistics, Per Capita, Underprivileged Area Score. Excerpt: Dynamic network analysis (DNA) is an emergent scientific field that Purchase includes free access to book updates online and a free trial membership in the publisher's book club where you can select from more than a million books without charge. Chapters: Social Weather Stations, Sexual Dimorphism Measures, Dynamic Network Analysis, Social Statistics, Network Probability Matrix, Social Network Change Detection, Economic Statistics, Per Capita, Underprivileged Area Score. Excerpt: Dynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA) and multi-agent systems (MAS) within network science and network theory. There are two aspects of this field. The first is the statistical analysis of DNA data. The second is the utilization of simulation to address issues of network dynamics. DNA networks vary from traditional social networks in that they are larger, dynamic, multi-mode, multi-plex networks, and may contain varying levels of uncertainty. DNA statistical tools are generally optimized for large-scale networks and admit the analysis of multiple networks simultaneously in which, there are multiple types of nodes (multi-node) and multiple types of links (multi-plex). In contrast, SNA statistical tools focus on single or at most two mode data and facilitate the analysis of only one type of link at a time. DNA statistical tools tend to provide more measures to the user, because they have measures that use data drawn from multiple networks simultaneously. From a computer simulation perspective, nodes in DNA are like atoms in quantum theory, nodes can be, though need not be, treated as probabilistic. Whereas nodes in a traditional SNA model are static, nodes in a DNA model have the ability to learn. Properties change over time; nodes can adapt: A company's employees can learn new skills and increase their value to the network; Or, capture one terrorist and three more are forced to improvise. Change propagates from one node to the next and Books, , Social-Statistics~~Books-Llc, 999999999, Social Statistics, Books Llc, 1156606799, General Books LLC, , , , , General Books LLC<

ISBN: 9781156606797

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