A Supervised Machine Learning Study of Online Discussion Forums about Type-2 Diabetes

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings

As an instance of online communities, online diabetes discussion forums mirror these characteristics and seem to track the growing impact of diabetes on individuals around the world. In this paper, we first systematically collected texts
from online discussion forums about diabetes and then applied supervised machine learning techniques to analyze the online conversations. In order to analyse these online textual conversations, we have chosen four domain specific models (Emotions, Sentiment, Personality Traits and Patient Journey). As part of text classification, we employed the ensemble learning method by using 5 different supervised machine learning algorithms to build a set of text classifiers by using the voting method to predict most probable label for a given textual conversation from the online discussion forums. Our findings show that there is a high amount of trust expressed by a subset of users and these users play a vital role in supporting other users of the online discussion forums about diabetes.

Publication information

Original languageEnglish
Title of host publication2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom)
EditorsHsi Pin Ma, Baofeng Wang
Place of PublicationLos Alamos, CA
Publication date2017
ISBN (Print)9781509067039, 9781509067053
ISBN (Electronic)9781509067046
StatePublished - 2017
EventIEEE Healthcom 17 - Dalian, China
Duration: 12 Oct 201715 Oct 2017
Conference number: 19


ConferenceIEEE Healthcom 17
SponsorDalian University

Bibliographical note

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ID: 50344034