Understanding characteristics of semantic associations in health consumer generated knowledge representation in social media

Min Sook Park

Journal of the Association for Information Science & Technology, 2019, vol. 70, issue 11, 1210-1222

Abstract: This study explores knowledge organization behavior on the Web with respect to identifying the semantic relationships of health‐related concepts. In particular, this study aims to investigate the potentials of imparting richer collective intelligence to existing knowledge representation systems in health. The study focuses on detecting semantic relationships between semantic groups of major concepts mined from health consumers' descriptions of health issues and associated user‐generated metadata (i.e., tags). A total of 50,263 blogs and associated 341,720 tags were collected from Tumblr, a blogging social networking site. Text mining and semantic network analysis methods were used to explore the usage patterns at semantic type levels of the identified medical concepts in tags, in blogs, and between tags and blogs. More various associations among semantic types were identified both in tags and in blogs. These associations were more diverse and complicated than the relationships in the Unified Medical Language System Semantic Network. Among the groups of concepts in tags and blogs, groups showed relatively stronger and more diverse relationships with other groups of concepts. In addition, many direct and close relations were found between tags and blogs.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asi.24198

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:70:y:2019:i:11:p:1210-1222

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635

Access Statistics for this article

More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().