title: Characterizing the sublanguage of online breast cancer forums for medications, symptoms, and emotions.
abstract: Online health communities play an increasingly prevalent role for patients and are the source of a growing body of research. A lexicon that represents the sublanguage of an online community is an important resource to enable analysis and tool development over this data source. This paper investigates a method to generate a lexicon representative of the language of members in a given community with respect to specific semantic types. We experiment with a breast cancer community and detect terms that belong to three semantic types: medications, symptoms and side effects, and emotions. We assess the ability of our automatically generated lexicons to detect new terms, and show that a data-driven approach captures the sublanguage of members in these communities, all the while increasing coverage of general-purpose terminologies. The code and the generated lexicons are made available to the research community.
authors.affiliation: Columbia University, New York, NY.
authors.forename: Noémie
authors.initials: N
authors.lastname: Elhadad
authors.affiliation: Columbia University, New York, NY.
authors.forename: Shaodian
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Columbia University, New York, NY.
authors.forename: Patricia
authors.initials: P
authors.lastname: Driscoll
authors.affiliation: Google, Inc., New York, NY.
authors.forename: Samuel
authors.initials: S
authors.lastname: Brody
mesh_terms: D001943:Breast Neoplasms; D005260:Female; D006801:Humans; D020407:Internet; D012657:Self-Help Groups; D012660:Semantics; D014825:Vocabulary