Healthcare Social Question Answering: Concept Mapping and Cluster Analysis based on Graph Theory
| dc.contributor.author | Blooma, Mohan John | en_NZ |
| dc.contributor.author | Huy, Tran Duc | en_NZ |
| dc.contributor.author | Wickramasinghe, Nilmini | en_NZ |
| dc.date.accessioned | 2014-12-04T01:20:20Z | |
| dc.date.available | 2014-12-04T01:20:20Z | |
| dc.date.copyright | 2014 | en_NZ |
| dc.date.issued | 2014 | en_NZ |
| dc.description.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. | en_NZ |
| dc.identifier.citation | Proceedings of the 25th Australasian Conference on Information Systems, 8th - 10th December, Auckland, New Zealand | |
| dc.identifier.isbn | 978-1-927184-26-4 | |
| dc.identifier.uri | https://hdl.handle.net/10292/8169 | |
| dc.publisher | ACIS | |
| dc.rights.accessrights | OpenAccess | |
| dc.title | Healthcare Social Question Answering: Concept Mapping and Cluster Analysis based on Graph Theory | en_NZ |
| dc.type | Conference Contribution |
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