The Assessment of Twitter's Potential for Outbreak Detection: Avian Influenza Case Study.

ABSTRACT: Social media services such as Twitter are valuable sources of information for surveillance systems. A digital syndromic surveillance system has several advantages including its ability to overcome the problem of time delay in traditional surveillance systems. Despite the progress made with using digital syndromic surveillance systems, the possibility of tracking avian influenza (AI) using online sources has not been fully explored. In this study, a Twitter-based data analysis framework was developed to automatically monitor avian influenza outbreaks in a real-time manner. The framework was implemented to find worrisome posts and alerting news on Twitter, filter irrelevant ones, and detect the onset of outbreaks in several countries. The system collected and analyzed over 209,000 posts disc

SUBMITTER: Yousefinaghani S 

PROVIDER: S-EPMC6890696 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature