Melanie J Martin1. 1. Computer Science Department, California State University, Stanislaus, One University Circle, Turlock California, 95382, USA. mmartin@cs.csustan.edu.
Abstract
BACKGROUND: In this paper we present a detailed scheme for annotating medical web pages designed for health care consumers. The annotation is along two axes: first, by reliability (the extent to which the medical information on the page can be trusted), second, by the type of page (patient leaflet, commercial, link, medical article, testimonial, or support). RESULTS: We analyze inter-rater agreement among three judges for each axis. Inter-rater agreement was moderate (0.77 accuracy, 0.62 F-measure, 0.49 Kappa) on the page reliability axis and good (0.81 accuracy, 0.72 F-measure, 0.73 Kappa) along the page type axis. CONCLUSIONS: We have shown promising results in this study that appropriate classes of pages can be developed and used by human annotators to annotate web pages with reasonable to good agreement. AVAILABILITY: No.
BACKGROUND: In this paper we present a detailed scheme for annotating medical web pages designed for health care consumers. The annotation is along two axes: first, by reliability (the extent to which the medical information on the page can be trusted), second, by the type of page (patient leaflet, commercial, link, medical article, testimonial, or support). RESULTS: We analyze inter-rater agreement among three judges for each axis. Inter-rater agreement was moderate (0.77 accuracy, 0.62 F-measure, 0.49 Kappa) on the page reliability axis and good (0.81 accuracy, 0.72 F-measure, 0.73 Kappa) along the page type axis. CONCLUSIONS: We have shown promising results in this study that appropriate classes of pages can be developed and used by human annotators to annotate web pages with reasonable to good agreement. AVAILABILITY: No.