Analysis and Evaluation of Social Network Anomaly Detection

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dc.contributor.authorZhao, Meng Johnen
dc.contributor.committeechairWoodall, William H.en
dc.contributor.committeechairDriscoll, Anne R.en
dc.contributor.committeememberStevens, Nathaniel T.en
dc.contributor.committeememberFricker, Ronald D. Jr.en
dc.contributor.committeememberSengupta, Srijanen
dc.contributor.departmentStatisticsen
dc.date.accessioned2017-10-28T08:00:19Zen
dc.date.available2017-10-28T08:00:19Zen
dc.date.issued2017-10-27en
dc.description.abstractAs social networks become more prevalent, there is significant interest in studying these network data, the focus often being on detecting anomalous events. This area of research is referred to as social network surveillance or social network change detection. While there are a variety of proposed methods suitable for different monitoring situations, two important issues have yet to be completely addressed in network surveillance literature. First, performance assessments using simulated data to evaluate the statistical performance of a particular method. Second, the study of aggregated data in social network surveillance. The research presented tackle these issues in two parts, evaluation of a popular anomaly detection method and investigation of the effects of different aggregation levels on network anomaly detection.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:12688en
dc.identifier.urihttp://hdl.handle.net/10919/79849en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectchange detectionen
dc.subjectErdos-Renyi modelen
dc.subjectmoving windowen
dc.subjectsocial networken
dc.subjectstandardizationen
dc.subjectstatistical process monitoringen
dc.subjectaggregationen
dc.subjectDCSBMen
dc.subjectscan methoden
dc.titleAnalysis and Evaluation of Social Network Anomaly Detectionen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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