Annotating Patient Information Needs in Online Diabetes Forums

Julia Romberg, Jan Dyczmons, Sandra Olivia Borgmann, Jana Sommer, Markus Vomhof, Cecilia Brunoni, Ismael Bruck-Ramisch, Luis Enders, Andrea Icks, Stefan Conrad


Abstract
Identifying patient information needs is an important issue for health care services and implementation of patient-centered care. A relevant number of people with diabetes mellitus experience a need for information during the course of the disease. Health-related online forums are a promising option for researching relevant information needs closely related to everyday life. In this paper, we present a novel data corpus comprising 4,664 contributions from an online diabetes forum in German language. Two annotation tasks were implemented. First, the contributions were categorised according to whether they contain a diabetes-specific information need or not, which might either be a non diabetes-specific information need or no information need at all, resulting in an agreement of 0.89 (Krippendorff’s α). Moreover, the textual content of diabetes-specific information needs was segmented and labeled using a well-founded definition of health-related information needs, which achieved a promising agreement of 0.82 (Krippendorff’s αu). We further report a baseline for two sub-tasks of the information extraction system planned for the long term: contribution categorization and segment classification.
Anthology ID:
2020.smm4h-1.3
Volume:
Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venues:
COLING | SMM4H
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Publisher:
Association for Computational Linguistics
Note:
Pages:
19–26
Language:
URL:
https://aclanthology.org/2020.smm4h-1.3
DOI:
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Cite (ACL):
Julia Romberg, Jan Dyczmons, Sandra Olivia Borgmann, Jana Sommer, Markus Vomhof, Cecilia Brunoni, Ismael Bruck-Ramisch, Luis Enders, Andrea Icks, and Stefan Conrad. 2020. Annotating Patient Information Needs in Online Diabetes Forums. In Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, pages 19–26, Barcelona, Spain (Online). Association for Computational Linguistics.
Cite (Informal):
Annotating Patient Information Needs in Online Diabetes Forums (Romberg et al., SMM4H 2020)
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https://aclanthology.org/2020.smm4h-1.3.pdf