Twitter catches the flu: detecting influenza epidemics using Twitter
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Epidemic outbreak and spread detection system based on twitter data
HIS'12 Proceedings of the First international conference on Health Information Science
Towards context-aware search and analysis on social media data
Proceedings of the 16th International Conference on Extending Database Technology
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West Nile virus (WNV) is one of the most geographically widespread arboviruses in the world with cases occurring on all continents except Antarctica. The goal of study is to understand a real-time spatial temporal WNV activity using Twitter data. In our study, we collected tweets for the entire world using Twitter Search API with tags #WestNileVirus, and #WNV from August 31, 2011. Collected tweets were stored, cleaned, and geocoded. The Google API was used to display information on the web. The changes per week showed that the numbers were relatively high from August through October then gradually slowed down from December through March. We also found a very large increase in tweet numbers from March and April. This may be due to unusual higher temperature and mosquito activities in March and April this year compared to previous years.