title: Analyzing Self-Help Forums with Ontology-Based Text Mining: An Exploration in Kidney Space.
abstract: The Internet has emerged as a popular source for health-related information. More than eighty percent of American Internet users have searched for health topics online. Millions of patients use self-help online forums to exchange information and support. In parallel, the increasing prevalence of chronic diseases has become a financial burden for the healthcare system demanding new, cost-effective interventions. To provide such interventions, it is necessary to understand patients' preferences of treatment options and to gain insights into their experiences as patients. We introduce a text-processing algorithm based on semantic ontologies to allow for finer-grained analyses of online forums compared to standard methods. We have applied our method in an analysis of two major Chronic Kidney Disease (CKD) forums. Our results suggest that the analysis of forums may provide valuable insights on daily issues patients face, their choice of different treatment options and interactions between patients, their relatives and clinicians.
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Philipp
authors.initials: P
authors.lastname: Burckhardt
authors.affiliation: Carnegie Mellon University, Pittsburgh, PA.
authors.forename: Rema
authors.initials: R
authors.lastname: Padman
mesh_terms: D002908:Chronic Disease; D057225:Data Mining; D015438:Health Behavior; D006801:Humans; D020407:Internet; D012657:Self-Help Groups