The statistics of topic modelling.

dc.contributor.authorAbey, Rebecca
dc.date.accessioned2015-10-20T00:09:53Z
dc.date.available2015-10-20T00:09:53Z
dc.date.issued2015en
dc.description.abstractThis research project aims to provide a clear and concise guide to latent dirichlet allocation which is a form of topic modelling. The aim is to help researchers who do not have a strong background in mathematics or statistics to feel comfortable with using topic modelling in their work. In order to achieve this, the thesis provides a step-by-step explanation of how topic modelling works. A range of tools that can be used to perform a topic model analysis are also described. The first chapter gives an explanation of how topic modelling, and (more specifically), latent dirichlet allocation works; it offers a very basic explanation and then provides an easy to follow mathematical explanation. The second chapter explains how to perform a topic model analysis; this is done through an explanation of each step used to run a topic model analysis, starting from the type of dataset through to the software packages available to use. The third section provides an example topic model analysis, based on the Philpapers dataset. The final section provides a discussion on the highlights of each chapter and areas for further research.en
dc.identifier.urihttp://hdl.handle.net/10092/11264
dc.identifier.urihttp://dx.doi.org/10.26021/9168
dc.language.isoen
dc.publisherUniversity of Canterbury. Mathematics and Statisticsen
dc.relation.isreferencedbyNZCUen
dc.rightsCopyright Rebecca Abeyen
dc.rights.urihttps://canterbury.libguides.com/rights/thesesen
dc.subjectstatisticsen
dc.subjecttopic modellingen
dc.subjecttext analysisen
dc.titleThe statistics of topic modelling.en
dc.typeTheses / Dissertations
thesis.degree.disciplineStatistics
thesis.degree.grantorUniversity of Canterburyen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Scienceen
uc.bibnumber2127196
uc.collegeFaculty of Scienceen
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