Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza

VM Dukic, 2009, Tracking Flu Epidemics Using Google Flu Trends and Particle Learning, Social Science Research Network

AF Dugas, 2013, Influenza Forecasting with Google Flu Trends, PLoS ONE, 8, e56176, 10.1371/journal.pone.0056176

D Olson, 2013, Reassessing Google Flu Trends Data for Detection of Seasonal and Pandemic Influenza: A Comparative Epidemiological Study at Three Geographic Scales, PLoS Computational Biology, 9, e1003256, 10.1371/journal.pcbi.1003256

D Butler, 2013, When Google got Flu Wrong, Nature, 494, 155, 10.1038/494155a

S Newsam, 2010, Crowdsourcing What Is Where: Community-Contributed Photos as Volunteered Geographic Information, IEEE Multimedia: Special Issue on Mining Community-Contributed Multimedia, 17, 36, 10.1109/MMUL.2010.79

Perreault, M, Ruths D. The Effect of Mobile Platforms on Twitter Content Generation. In Proc. of the International Conference on Social Media and Weblogs. 2011.

SA Golder, 2011, Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength across Diverse Cultures, Science, 333, 1878, 10.1126/science.1202775

AC Nagel, 2013, The Complex Relationship of Realspace Events and Messages in Cyberspace: Case Study of Influenza and Pertussis Using Tweets, Journal of Medical Internet Research, 15, e237, 10.2196/jmir.2705

A Lamb, 2013, Separating Fact from Fear: Tracking Flu Infections on Twitter, In Proc. of NAACL-HLT, 789

M Tsou, 2013, Editorial: Visualization of Social Media: Seeing a Mirage or a Message? In Special Content Issue: Mapping Cyberspace and Social Media, Cartography and Geographic Information Science, 40, 55, 10.1080/15230406.2013.776754

M Tsou, 2013, Mapping Social Activities and Concepts with Social Media (Twitter) and Web Search Engines (Yahoo and Bing): A Case Study in 2012 U.S. Presidential Election, Cartography and Geographic Information Science, 40, 337, 10.1080/15230406.2013.799738

Joachims T. Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In Proc. of the European Conference on Machine Learning (ECML). Springer. 1998.

G Salton, 1988, Term-Weighting Approaches in Automatic Text Retrieval, Information Processing & Management, 24, 513, 10.1016/0306-4573(88)90021-0

AA Aslam, 2014, The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance, J Med Internet Res, 16, e250, 10.2196/jmir.3532

A Petróczi, 2012, The Doping Self-Reporting Game: The Paradox of a ‘false-Telling’ Mechanism and Its Potential Research and Policy Implications, 15, 513