Document Type
Conference Proceeding
Publication Date
11-2014
Abstract
Since the early 2000’s, Internet usage for health information searching has increased significantly. Studying search queries can help us to understand users “information need” and how do they formulate search queries (“expression of information need”). Although cardiovascular diseases (CVD) affect a large percentage of the population, few studies have investigated how and what users search for CVD. We address this knowledge gap in the community by analyzing a large corpus of 10 million CVD related search queries from MayoClinic.com. Using UMLS MetaMap and UMLS semantic types/concepts, we developed a rule-based approach to categorize the queries into 14 health categories. We analyzed structural properties, types (keyword-based/Wh-questions/Yes-No questions) and linguistic structure of the queries. Our results show that the most searched health categories are ‘Diseases/Conditions’, ‘Vital- Sings’, ‘Symptoms’ and ‘Living-with’. CVD queries are longer and are predominantly keyword-based. This study extends our knowledge about online health information searching and provides useful insights for Web search engines and health websites.
Repository Citation
Jadhav, A. S.,
Sheth, A. P.,
& Pathak, J.
(2014). Online Information Searching for Cardiovascular Diseases: An Analysis of Mayo Clinic Search Query Logs. .
https://corescholar.libraries.wright.edu/knoesis/539
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
To be presented at the American Medical Informatics Association Annual Symposium, November 15-19, 2014.