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dc.contributor.advisorOtero, Carlos
dc.contributor.authorMjhool, Ahmed Yaseen
dc.date.accessioned2017-01-12T20:11:22Z
dc.date.available2017-01-12T20:11:22Z
dc.date.issued2016-12
dc.identifier.urihttp://hdl.handle.net/11141/1133
dc.descriptionThesis (M.S.) - Florida Institute of Technology, 2016en_US
dc.description.abstractIn mobile system environments, the quality perceived by users is inconstant and reliant on many factors such as cellular network, data connection, cost, coverage area, etc. Even though Quality of Service (QoS) management is enabled in most modern telecommunication systems, it does not guarantee the actual user’s perceived Quality of Experience (QoE) level. Many cellular networks rely on engineering test research, such as drive testing or smart mobile applications, to collect the required parameters in order to provide better service quality to users. However, this approach does not always yield customer satisfaction. Hence, user opinions should be considered. These opinions can be found via social media, and collected and processed via social media analytics models. In this thesis research, a Rule-based algorithm is implemented. Based on this Rulebased algorithm, a sentiment analyzer is designed and tested. The results from testing the Rule-based algorithm are compared with results from a Naïve Bayes analyzer. In this thesis, the carrier Verizon is considered as the main topic and Twitter is considered the data source. This Rule-based algorithm and analyzer introduces a new method for generating datasets to easily design sentiment models. These models will analyze users’ opinions to make better decisions and recommend the optimal QoE solutions. The results of research conducted in this thesis show that the Rule-based analyzer performs better than the Naïve Bayes analyzer.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.rightsCopyright held by author.en_US
dc.titleEvaluation of User Perceived QoE in Mobile Systems Using Social Media Analyticsen_US
dc.typeThesisen_US
dc.date.updated2017-01-10T16:20:09Z
thesis.degree.nameMaster of Science In Computer Engineeringen_US
thesis.degree.levelMastersen_US
thesis.degree.disciplineComputer Engineeringen_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.grantorFlorida Institute of Technologyen_US
dc.type.materialtext


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