Paper Info
Title
Supporting temporal analytics for health-related events in microblogs
Abstract
Microblogging services, such as Twitter, are gaining interests as a means of sharing information in social networks. Numerous works have shown the potential of using Twitter posts (or tweets) in order to infer the existence and magnitude of real-world events. In the medical domain, there has been a surge in detecting public health related tweets for early warning so that a rapid response from health authorities can take place. In this paper, we present a temporal analytics tool for supporting a comparative, temporal analysis of disease outbreaks between Twitter and official sources, such as, World Health Organization (WHO) and ProMED-mail. We automatically extract and aggregate outbreak events from official outbreak reports, producing time series data. Our tool can support a correlation analysis and an understanding of the temporal developments of outbreak mentions in Twitter, based on comparisons with official sources.
Year
DOI
Venue
2012
10.1145/2396761.2398726
CIKM
Keywords
Field
DocType
health authority,official outbreak report,health-related event,twitter post,aggregate outbreak event,temporal analytics tool,correlation analysis,disease outbreak,official source,temporal analysis,temporal development,time series analysis
Public health,Warning system,Data science,Data mining,World Wide Web,Social media,Social network,Computer science,Microblogging,Analytics,Correlation analysis
Conference
Citations 
PageRank 
References 
7
0.47
6
Authors
4
Name
Order
Citations
PageRank
Nattiya Kanhabua134626.35
Sara Romano2222.75
Avaré Stewart311110.56
Wolfgang Nejdl46633556.13