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Automatic Classification of Forum Posts: A Finnish Online Health Discussion Forum Case

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationEMBEC and NBC 2017 - Joint Conference of the European Medical and Biological Engineering Conference EMBEC 2017 and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, NBC 2017
PublisherSpringer Verlag
Pages169-172
Number of pages4
ISBN (Electronic)978-981-10-5122-7
ISBN (Print)978-981-10-5121-0
DOIs
Publication statusPublished - 2018
Publication typeA4 Article in a conference publication
EventJoint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) -
Duration: 1 Jan 1900 → …

Publication series

NameIFMBE Proceedings
Volume65
ISSN (Electronic)1680-0737

Conference

ConferenceJoint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC)
Period1/01/00 → …

Abstract

Online health discussion forums play a key role in accessing, distributing and exchanging health information at an individual and societal level. Due to their free nature, using and regulating these forums require substantial amount of manual effort. In this study, we propose a computational approach, i.e., a machine learning framework, in order to categorize the messages from Finland’s largest online health discussion forum into 16 categories. An accuracy of 70.8% was obtained with a Naïve Bayes classifier, applied on term frequency-inverse document frequency features.

Keywords

  • Machine learning, topic classification, Social Media, online discussion forum, Natural language processing

Publication forum classification

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