A Scalable Framework to Detect Personal Health Mentions on Twitter

A scalable framework to detect personal health status mentions on Twitter and assess the extent to which such information is disclosed, finding that tweets from a small subset of the health issues can train a scalable classifier to detect health mentions.

Abstract

It is possible to automatically detect personal health status mentions on Twitter in a scalable manner. These mentions correspond to the health issues of the Twitter users themselves, but also other individuals. Though this study did not investigate the veracity of such statements, we anticipate such information may be useful in supplementing traditional health-related sources for research purposes.