Vis enkel innførsel

dc.contributor.advisorGulla, Jon Atlenb_NO
dc.contributor.advisorWei, Weinb_NO
dc.contributor.advisorØhrn, Aleksandernb_NO
dc.contributor.authorNordvik, Henriknb_NO
dc.date.accessioned2014-12-19T13:37:55Z
dc.date.available2014-12-19T13:37:55Z
dc.date.created2011-10-19nb_NO
dc.date.issued2011nb_NO
dc.identifier449015nb_NO
dc.identifierntnudaim:6064nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/252664
dc.description.abstractSentiment analysis is the problem of determining the attitude or feelings atext tries to convey. It has recently received a lot of focus, one reason beingthat the amount of text containing personal opinions has increased in stepwith the emergence of social media.We implement and evaluate a supervised, unsupervised and a hybrid methodfor classifying the sentiment of a document. We find that for the super-vised method, the most important aspect is how we select which featuresto use, and which to discard.Out of the systems we evaluated, the supervised method clearly performedthe best. The Na ̈ve Bayes algorithm managed to get the best performanceıon our test sets, with an accuracy of 98.3% on one test set, and 90.5% on amore difficult set.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:6064no_NO
dc.subjectMTDT datateknikkno_NO
dc.subjectData- og informasjonsforvaltningno_NO
dc.titleSentiment Analysisnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber54nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


Tilhørende fil(er)

Thumbnail
Thumbnail
Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel