User-centered design of a web-based crowdsourcing-integrated semantic text annotation tool for building a mental health knowledge base.

ABSTRACT:

Background

One in five U.S. adults lives with some kind of mental health condition and 4.6% of all U.S. adults have a serious mental illness. The Internet has become the first place for these people to seek online mental health information for help. However, online mental health information is not well-organized and often of low quality. There have been efforts in building evidence-based mental health knowledgebases curated with information manually extracted from the high-quality scientific literature. Manual extraction is inefficient. Crowdsourcing can potentially be a low-cost mechanism to collect labeled data from non-expert laypeople. However, there is not an existing annotation tool integrated with popular crowdsourcing platforms to perform the information extraction tasks. I

SUBMITTER: He X 

PROVIDER: S-EPMC7577935 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature