Conference paper
Identifying Similar Questions in Healthcare Social Question Answering: A Design Science Research
Proceedings of the 24th Americas Conference on Information Systems, pp.1-10
Americas Conference on Information Systems, 24th (New Orleans, United States, 16-Aug-2018–18-Aug-2018)
Association for Information Systems
2018
Abstract
Healthcare Social Question Answering (SQA) are services where users can ask, respond and receive answers for their posts from other social media users in health domain. The activities of social media users such as asking, responding, liking and posting comments results in building reusable content. This study identifies similar content (i.e. questions) from user posts which contributes towards providing better health care services. For identifying similar questions, this study uses a quadri-link cluster analysis to analyze the attributes of questions, answers and users. A design science methodology was used to develop the algorithm and calculate the similarity measures. The results of cluster analysis based on the proposed similarity measures on a pilot data set indicate that identifying similar questions will be a contribution in the transition of traditional healthcare services into social media enabled healthcare services. The results exemplify the future of digital transformation in health care SQA.
Details
- Title
- Identifying Similar Questions in Healthcare Social Question Answering: A Design Science Research
- Authors
- Blooma John (Author) - University of CanberraNilmini Wickramasinghe (Author) - Deakin UniversityJayan Kurian (Author) - University of Canberra
- Publication details
- Proceedings of the 24th Americas Conference on Information Systems, pp.1-10
- Conference details
- Americas Conference on Information Systems, 24th (New Orleans, United States, 16-Aug-2018–18-Aug-2018)
- Publisher
- Association for Information Systems
- Date published
- 2018
- Organisation Unit
- University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99548307102621
- Output Type
- Conference paper
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