Show simple item record

dc.contributor.advisorBrady, Alyce
dc.contributor.advisorRichey, MIchael
dc.contributor.authorHudson, Bo
dc.date.accessioned2016-05-21T16:17:33Z
dc.date.available2016-05-21T16:17:33Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10920/30388
dc.descriptioniii, 28 p.en_US
dc.description.abstractThe goal of this project was to build a sentiment analysis classification based upon Machine Learning. The classification of Twitter tweets and Facebook comments allow for better marketing analysis while also saving an incredible amount of time. Four separate ensemble classification methods were tweaked and tested until the single best classification method we employed was found.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofSenior Individualized Projects. Computer Science.
dc.relation.ispartofKalamazoo College Computer Science Senior Individualized Projects Collection
dc.rightsU.S. copyright laws protect this material. Commercial use or distribution of this material is not permitted without prior written
dc.titleSentiment Analysis : Building and Testing Four Ensemble Classification Methodsen_US
dc.typeThesisen_US
KCollege.Access.ContactIf you are not a current Kalamazoo College student, faculty, or staff member, email dspace@kzoo.edu to request access to this thesis.


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Computer Science Senior Individualized Projects [211]
    This collection includes Senior Individualized Projects (SIP's) completed in the Computer Science Department. Abstracts are generally available to the public, but PDF files are available only to current Kalamazoo College students, faculty, and staff.

Show simple item record