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dc.contributor.advisorZhao, J. Leonen_US
dc.contributor.authorHu, Daningen_US
dc.creatorHu, Daningen_US
dc.date.accessioned2011-10-18T18:27:32Z
dc.date.available2011-10-18T18:27:32Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/10150/145710
dc.description.abstractNowadays people and organizations are more and more interconnected in the forms of social networks: the nodes are social entities and the links are various relationships among them. The social network theory and the methods of social network analysis (SNA) are being increasingly used to study such real-world networks in order to support knowledge management and decision making in organizations. However, most existing social network studies focus on the static topologies of networks. The dynamic network link formation process is largely ignored. This dissertation is devoted to study such dynamic network formation process to support knowledge management and decision making in networked environments. Three challenges remain to be addressed in modeling and analyzing the dynamic network link formation processes. The first challenge is about modeling the network topological changes using longitudinal network data. The second challenge is concerned with examining factors that influence formation of links among individuals in networks. The third challenge is regarding link prediction in evolving social networks. This dissertation presents four essays that address these challenges in various knowledge management domains. The first essay studies the topological changes of a major international terrorist network over a 14-year period. In addition, this paper used a simulation approach to examine this network's vulnerability to random failures, targeted attacks, and real world authorities' counterattacks. The second essay and third essay focuses on examining determinants that significantly influence the link formation processes in social networks. The second essay found that mutual acquaintance and vehicle affiliations facilitate future co-offending link formation in a real-world criminal network. The third essay found that homophily in programming language preference, and mutual are determinants for forming participation links in an online Open Source social network. The fourth essay focuses on the link prediction in evolving social networks. It proposes a novel infrastructure for describing and utilizing the discovered determinants of link formation process (i.e. semantics of social networks) in link prediction to support expert recommendation application in an Open Source developer community. It is found that the integrated mechanism outperforms either user-based or Top-N most recognized mechanism.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectExpert Recommendation Systemsen_US
dc.subjectOpen Source Software Communityen_US
dc.subjectSecurity Informaticsen_US
dc.subjectSocial Network Formationen_US
dc.titleAnalysis and Applications of Social Network Formationen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.identifier.oclc659752297
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberNunamaker, Jay F.en_US
dc.contributor.committeememberZhang, Zhuen_US
dc.description.releaseEmbargo: Release after 7/15/2011en_US
dc.identifier.proquest10560
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineManagement Information Systemsen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-08-22T08:39:59Z
html.description.abstractNowadays people and organizations are more and more interconnected in the forms of social networks: the nodes are social entities and the links are various relationships among them. The social network theory and the methods of social network analysis (SNA) are being increasingly used to study such real-world networks in order to support knowledge management and decision making in organizations. However, most existing social network studies focus on the static topologies of networks. The dynamic network link formation process is largely ignored. This dissertation is devoted to study such dynamic network formation process to support knowledge management and decision making in networked environments. Three challenges remain to be addressed in modeling and analyzing the dynamic network link formation processes. The first challenge is about modeling the network topological changes using longitudinal network data. The second challenge is concerned with examining factors that influence formation of links among individuals in networks. The third challenge is regarding link prediction in evolving social networks. This dissertation presents four essays that address these challenges in various knowledge management domains. The first essay studies the topological changes of a major international terrorist network over a 14-year period. In addition, this paper used a simulation approach to examine this network's vulnerability to random failures, targeted attacks, and real world authorities' counterattacks. The second essay and third essay focuses on examining determinants that significantly influence the link formation processes in social networks. The second essay found that mutual acquaintance and vehicle affiliations facilitate future co-offending link formation in a real-world criminal network. The third essay found that homophily in programming language preference, and mutual are determinants for forming participation links in an online Open Source social network. The fourth essay focuses on the link prediction in evolving social networks. It proposes a novel infrastructure for describing and utilizing the discovered determinants of link formation process (i.e. semantics of social networks) in link prediction to support expert recommendation application in an Open Source developer community. It is found that the integrated mechanism outperforms either user-based or Top-N most recognized mechanism.


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