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.
|Title of host publication||24TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS|
|Subtitle of host publication||Healthcare Informatics & Health Information Technology (SIGHealth)|
|Place of Publication||USA|
|Publisher||Association for Information Systems|
|Number of pages||10|
|Publication status||Published - 15 Aug 2018|
|Event||24th Americas Conference on Information Systems - Hyatt Regency New Orleans, New Orleans, United States|
Duration: 16 Aug 2018 → 18 Aug 2018
|Conference||24th Americas Conference on Information Systems|
|Abbreviated title||AMCIS 2018|
|Period||16/08/18 → 18/08/18|
JOHN, B., Wickramasinghe, N., & KURIAN, J. C. (2018). Identifying Similar Questions in Healthcare Social Question Answering: A Design Science Research. In 24TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS: Healthcare Informatics & Health Information Technology (SIGHealth) (pp. 1-10). USA: Association for Information Systems.