Song, M. (2019). Health Social Network Analytics: Analysis of Chronic Diseases With Extracted Entities and Their Relations. Journal of Medical Internet Research, 21(6), e12876, 1-18.

https://www.jmir.org/2019/6/e12876/

Abstarct

Background: Social media platforms constitute a rich data source for natural language processing tasks such as named entity recognition, relation extraction, and sentiment analysis. In particular, social media platforms about health provide a different insight into patient’s experiences with diseases and treatment than those found in the scientific literature. Objective: This paper aimed to report a study of entities related to chronic diseases and their relation in user-generated text posts. The major focus of our research is the study of biomedical entities found in health social media platforms and their relations and the way people suffering from chronic diseases express themselves. Methods: We collected a corpus of 17,624 text posts from disease-specific subreddits of the social news and discussion website Reddit. For entity and relation extraction from this corpus, we employed the PKDE4J tool developed by Song et al (2015). PKDE4J is a text mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Results: Using PKDE4J, we extracted 2 types of entities and relations: biomedical entities and relations and subject-predicate-object entity relations. In total, 82,138 entities and 30,341 relation pairs were extracted from the Reddit dataset. The most highly mentioned entities were those related to oncological disease (2884 occurrences of cancer) and asthma (2180 occurrences). The relation pair anatomy-disease was the most frequent (5550 occurrences), the highest frequent entities in this pair being cancer and lymph. The manual validation of the extracted entities showed a very good performance of the system at the entity extraction task (3682/5151, 71.48% extracted entities were correctly labeled). Conclusions: This study showed that people are eager to share their personal experience with chronic diseases on social media platforms despite possible privacy and security issues. The results reported in this paper are promising and demonstrate the need for more in-depth studies on the way patients with chronic diseases express themselves on social media platforms.

연구의의

본 연구는 소셜미디어를 통해 사람들끼리 주고받는 질병 관련 정보들을 분석한 연구이다. 자연어로 이루어진 소셜미디어(Reddit) 데이터를 활용하여 개체명인식, 개체관계인식, 감성분석을 수행하였다. 본 연구에서는 개인의 경험을 공유하는 소셜 미디어 플랫폼의 특성에 초점을 맞추어 풍부한 분석을 수행하였다는 점에서 본 연구팀의 아젠다와 부합한다.