SYSTEMATIC REVIEW OF LITERATURE USING TWITTER AS A TOOL

dc.access.optionOpen Access
dc.contributor.advisorTabrizi, M. H. N
dc.contributor.authorPradyumn, Mudit
dc.contributor.departmentComputer Science
dc.date.accessioned2018-08-14T14:46:35Z
dc.date.available2018-08-14T14:46:35Z
dc.date.created2018-08
dc.date.issued2018-07-17
dc.date.submittedAugust 2018
dc.date.updated2018-08-09T20:01:17Z
dc.degree.departmentComputer Science
dc.degree.disciplineMS-Software Engineering
dc.degree.grantorEast Carolina University
dc.degree.levelMasters
dc.degree.nameM.S.
dc.description.abstractTwitter has over 330 million active monthly users producing roughly 500 million Tweets per day, or 200 billion Tweets a year. Making this one of the largest human-generated opinion data collections. In addition to this major advantage, Twitter generates real-time data, making it possible to gain insights on trending information instantaneously. People post about a wide variety of subjects, including their opinions, feelings, situations, current trends, and products. This makes it a great data source for analyzing the sentiments of people on a variety of subjects. In this study, out of 1025 research papers on Twitter data analytics from 2011-2017, papers from only 20 selected journals were considered for review. They were then classified based on their year of publication, their titles, data mining methods, and application areas. In the course of this study a tool for the Sentiment Analysis of the Twitter data was developed and used to conduct a case study on individuals on marijuana use during pregnancy.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10342/6950
dc.language.isoen
dc.publisherEast Carolina University
dc.subjectInsight
dc.subjectExtraction
dc.subjectClassification
dc.subjectSentiment Analysis
dc.subject.lcshTwitter--Analysis
dc.subject.lcshPregnant women--Drug use
dc.titleSYSTEMATIC REVIEW OF LITERATURE USING TWITTER AS A TOOL
dc.typeMaster's Thesis
dc.type.materialtext

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