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dc.contributor.advisorCaverlee, James
dc.creatorIbrahim Abdelhalim, Ashraf A.
dc.date.accessioned2016-04-06T16:52:07Z
dc.date.available2017-12-01T06:36:11Z
dc.date.created2015-12
dc.date.issued2016-01-04
dc.date.submittedDecember 2015
dc.identifier.urihttp://hdl.handle.net/1969.1/156300
dc.description.abstractThe goal of this work is to study the geographic propagation patterns of Twitters' hashtags. In order to analyze the hashtags' diffusion patterns, we look at the globe as a graph consists of a large grid of locations and use two different approaches to study the hashtags' behaviour. The first approach is to consider the locations on the global grid as variables (or features) and the individual hashtags as the examples. This viewpoint of our dataset allows us to perform dimensionality reduction techniques to reduce the size of the dataset without much loss of information and to identify the more influential locations. The second methodology is to transform the global grid into an undirected weighted graph and compute the influence curves associated with the hashtags propagation and their properties. We show that the influence curves of different classes of hashtags have similar patterns. In addition, we show that the influence curve can be approximated adequately using only six Chebychev polynomials.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectInformation Diffusion
dc.subjectdimensionality reduction
dc.titleAnalysis of Twitter Hashtags' Geographic Propagation
dc.typeThesis
thesis.degree.departmentComputer Science and Engineering
thesis.degree.disciplineComputer Science
thesis.degree.grantorTexas A & M University
thesis.degree.nameMaster of Science
thesis.degree.levelMasters
dc.contributor.committeeMemberFuruta, Richard
dc.contributor.committeeMemberGildin, Eduardo
dc.type.materialtext
dc.date.updated2016-04-06T16:52:07Z
local.embargo.terms2017-12-01
local.etdauthor.orcid0000-0002-4783-0912


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