Proceedings Abstracts of the Twenty-Third International Joint Conference on Artificial Intelligence

Detecting and Tracking Disease Outbreaks by Mining Social Media Data / 2958
Yusheng Xie, Zhengzhang Chen, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Alok Choudhary

The emergence and ubiquity of online social networks have enriched web data with evolving interactions and communities both at mega-scale and in real-time. This data offers an unprecedented opportunity for studying the interaction between society and disease outbreaks. The challenge we describe in this data paper is how to extract and leverage epidemic outbreak insights from massive amounts of social media data and how this exercise can benefit medical professionals, patients, and policymakers alike. We attempt to prepare the research community for this challenge with four datasets. Publishing the four datasets will commoditize the data infrastructure to allow a higher and more efficient focal point for the research community.