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.
| Original language | English (US) |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 85-93 |
| Number of pages | 9 |
| Volume | 6749 LNCS |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
| Event | Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2011 - Beijing, China Duration: Jul 9 2011 → Jul 9 2011 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6749 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2011 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 7/9/11 → 7/9/11 |
Fingerprint
Keywords
- geospatial analysis
- H1N1
- infectious diseases
- open source information
- surveillance
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
A geospatial analysis on the potential value of news comments in infectious disease surveillance. / Cui, Kainan; Cao, Zhidong; Zheng, Xiaolong; Zeng, Dajun; Zeng, Ke; Zheng, Min.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 6749 LNCS 2011. p. 85-93 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6749 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A geospatial analysis on the potential value of news comments in infectious disease surveillance
AU - Cui, Kainan
AU - Cao, Zhidong
AU - Zheng, Xiaolong
AU - Zeng, Dajun
AU - Zeng, Ke
AU - Zheng, Min
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - geospatial analysis
KW - H1N1
KW - infectious diseases
KW - open source information
KW - surveillance
UR - http://www.scopus.com/inward/record.url?scp=79960267034&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960267034&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22039-5_9
DO - 10.1007/978-3-642-22039-5_9
M3 - Conference contribution
AN - SCOPUS:79960267034
SN - 9783642220388
VL - 6749 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 85
EP - 93
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -