Identifying Similar Questions in Healthcare Social Question Answering: A Design Science Research

Blooma JOHN, Nilmini Wickramasinghe, Jayan Chirayath KURIAN

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

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.
Original languageEnglish
Title of host publication24TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS
Subtitle of host publicationHealthcare Informatics & Health Information Technology (SIGHealth)
Place of PublicationUSA
PublisherAssociation for Information Systems
Pages1-10
Number of pages10
ISBN (Print)9780996683166
Publication statusPublished - 15 Aug 2018
Event24th Americas Conference on Information Systems - Hyatt Regency New Orleans, New Orleans, United States
Duration: 16 Aug 201818 Aug 2018
https://amcis2018.aisconferences.org/

Conference

Conference24th Americas Conference on Information Systems
Abbreviated titleAMCIS 2018
Country/TerritoryUnited States
CityNew Orleans
Period16/08/1818/08/18
Internet address

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