Healthcare social question answering: Concept mapping and cluster analysis based on graph theory

Blooma JOHN, Nilmini Wickramasinghe

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)

Abstract

Healthcare Social Question Answering (SQA) services are dedicated platforms for users to freely ask questions regarding their health related concerns and respond to or rate other users’ questions. To have a deeper insight into harnessing the rich data collected in healthcare SQA services, this study aims to investigate the concepts discussed using the intricate web of social relationships among questions, answers, associated askers and answerers by applying graph theory, concept mapping and cluster analysis. We collected 4212 question from Drugs.com, one of the popular healthcare SQA services to visualise concepts using Leximancer and cluster similar questions using quadripartite graph-based cluster analysis. The findings demonstrate the openness demonstrated by users on their weight, sleep and drug related questions. The cluster analysis revealed the possibility of applying graph theory to identify similar questions.
Original languageEnglish
Title of host publicationProceedings of the 25th Australasian Conference on Information Systems
EditorsFelix B Tan Deborah Bunker
Place of PublicationOnline
PublisherACIS
Pages1-10
Number of pages10
ISBN (Print)9781927184264
Publication statusPublished - 2014
Externally publishedYes
Event25th Australasian Conference on Information Systems - Auckland, New Zealand
Duration: 8 Dec 201410 Dec 2014
http://bis2.aut.ac.nz/acis2014/ (Conference Link)

Conference

Conference25th Australasian Conference on Information Systems
Abbreviated titleACIS 2014
CountryNew Zealand
CityAuckland
Period8/12/1410/12/14
Internet address

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  • Cite this

    JOHN, B., & Wickramasinghe, N. (2014). Healthcare social question answering: Concept mapping and cluster analysis based on graph theory. In F. B. T. D. Bunker (Ed.), Proceedings of the 25th Australasian Conference on Information Systems (pp. 1-10). ACIS. http://hdl.handle.net/10292/8169