Identifying Topics for E-Cigarette User-Generated Contents: A Case Study From Multiple Social Media Platforms

• Published in: Journal of medical Internet research Vol. 19; no. 1; p. e24
• Main Authors: Zhan, Yongcheng, Liu, Ruoran, Li, Qiudan, Leischow, Scott James, Zeng, Daniel Dajun
• Format: Journal Article
• Language: English
• Published: Canada Journal of Medical Internet Research 01.01.2017; JMIR Publications
• Subjects: Case studies; Computational linguistics; Datasets as Topic; Electronic cigarettes; Electronic Nicotine Delivery Systems - statistics & numerical data; Humans; Internet; Language processing; Natural language interfaces; Original Paper; Social media; Social Media - statistics & numerical data; Social networks; Web site management software; Latent Dirichlet Allocation; topic modeling; social media; infodemiology; electronic cigarettes

Electronic cigarette (e-cigarette) is an emerging product with a rapid-growth market in recent years. Social media has become an important platform for information seeking and sharing. We aim to mine hidden topics from e-cigarette datasets collected from different social media platforms. This paper...