@inproceedings{5b69b17ad9f746d3916a3e31ac273cb5,
title = "A geospatial analysis on the potential value of news comments in infectious disease surveillance",
abstract = "With the development of Internet, widely kind of web data have been applied in influenza surveillance and epidemic early warning. However there were less works focusing on the estimation of geospatial distribution of influenza. In order to evaluate the potential power of news comments for geospatial distribution estimation, we choose the H1N1 pandemic in the mainland of China in 2009 as case. After collecting 75878 comments of H1N1 related news from www.sina.com(a famous news site in the mainland of China), we compared the geospatial distribution of comments against surveillance data. The result shows that the comments data share a similar geospatial distribution with the epidemic data(a correlation of 0.848 p<0.01), especially with a larger data volume(a correlation of 0.902 p<0.01). It suggests that extracting geospatial distribution from comments data for estimation could be an important supplementary method when the surveillance data are incomplete and unreliable.",
keywords = "H1N1, geospatial analysis, infectious diseases, open source information, surveillance",
author = "Kainan Cui and Zhidong Cao and Xiaolong Zheng and Daniel Zeng and Ke Zeng and Min Zheng",
year = "2011",
doi = "10.1007/978-3-642-22039-5_9",
language = "English (US)",
isbn = "9783642220388",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "85--93",
booktitle = "Intelligence and Security Informatics - Pacific Asia Workshop, PAISI 2011, Proceedings",
note = "Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2011 ; Conference date: 09-07-2011 Through 09-07-2011",
}