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Using Social Media Data to Understand Consumers' Information Needs and Emotions Regarding Cancer: Ontology-Based Data
Jooyun Lee1, Hyeoun-Ae Park2, Seul Ki Park2
1College of Nursing, Gachon University, Incheon, Republic of Korea.
Journal of Medical Internet Research
|December 7, 2020
Summary
Developing a cancer ontology from social media data revealed distinct information needs and emotions across cancer types. This enables tailored health information delivery for patients and their families.
Area of Science:
- Medical Informatics
- Computational Linguistics
- Public Health
Background:
- Social media analysis effectively identifies health information needs and emotional states related to diseases.
- Semantic analysis of social media data requires a structured ontology.
Purpose of the Study:
- To develop a cancer ontology incorporating consumer terminology.
- To analyze social media data for cancer-related health information needs and emotions.
Main Methods:
- A cancer ontology was created using South Korean social media data (online communities, blogs) from 2014-2017.
- Ontology-driven natural language processing (NLP) analyzed 754,744 cancer-related posts.
- Relative frequencies of ontology concepts were compared across different cancer types.
Main Results:
- The developed ontology includes 9 superclasses, 213 class concepts, and 4061 synonyms.
- Most frequent cancers mentioned were colon, breast, stomach, cervical, lung, liver, pancreatic, prostate, brain tumors, and leukemia.
- Top ontology concepts included risk factors, emotions, symptoms, treatments, and coping mechanisms.
Conclusions:
- Health information needs and emotions vary significantly by cancer type.
- Findings support providing personalized information tailored to specific cancer types and care stages.
- Cancer information dissemination should extend beyond patients to include families and the general public.
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