Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge

AbstractIn this paper we present a procedure to extract posts that contain experiential knowledge from Facebook discussions in Dutch, using automated filtering, manual annotations and machine learning. We define guidelines to annotate experiential knowledge and test them on a subset of the data. After several rounds of (re-)annotations, we come to an inter-annotator agreement of K=0.69, which reflects the difficulty of the task. We subsequently discuss inclusion and exclusion criteria to cope with the diversity of manifestations of experiential knowledge relevant to guideline development.