Big data analytics toolkit for business data based on social network analysis

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dc.contributor.advisorDu, Weichang
dc.contributor.authorLiang, Fan
dc.date.accessioned2023-03-01T16:18:34Z
dc.date.available2023-03-01T16:18:34Z
dc.date.issued2016
dc.date.updated2020-11-25T00:00:00Z
dc.description.abstractSocial network analysis (SNA) measures the relationships and structures with a set of metrics by building graphs for capturing in uential actors and patterns. In this thesis, we investigate the SNA approaches for solving real-world business applications, and propose a general-purpose software system that combines big data analytics and social network analysis techniques. The system's work ow consists of data collection, graph generation, graph reuse, network property calculation, SNA result interpretation, and application integration. The system operations are executable in a Hadoop-based distributed cluster with high throughput on large-scale data. We evaluate our prototype system with a case study on stock network. The result shows that the system is capable of analyzing business data at-scale and using SNA approach to solve business problems.
dc.description.copyright© Fan Liang, 2016
dc.formattext/xml
dc.format.extentx, 90 pages
dc.format.mediumelectronic
dc.identifier.otherThesis 9828
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/13437
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.titleBig data analytics toolkit for business data based on social network analysis
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.fullnameMaster of Computer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

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