TY - GEN
T1 - FluMapper
T2 - Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2013
AU - Padmanabhan, Anand
AU - Wang, Shaowen
AU - Cao, Guofeng
AU - Hwang, Myunghwa
AU - Zhao, Yanli
AU - Zhang, Zhenhua
AU - Gao, Yizhao
PY - 2013
Y1 - 2013
N2 - Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].
AB - Social media, such as social network (e.g., Facebook), microblogs (e.g. Twitter) have experienced a spectacular rise in popularity, and attracting hundreds of millions of users generating unprecedented amount of information. Twitter, for example, has rapidly gained approximately 500 million registered users as of 2012, generating 340 million tweets daily. Although each tweet is limited to only 140 characters, the aggregate of millions of tweets may provide a realistic representation of landscapes for a certain topic of interest. Furthermore, with widespread use of location aware mobile devices, users are sharing their whereabouts through social media services. This has resulted in a dramatic increase in volume of spatial data and they are becoming a crucial attribute of social media. These location-based social media thus could provide valuable insights to understanding many geographic phenomena. Recent studies capitalizing on social networking and media data show significant societal impacts, in many areas including infectious disease tracking [1].
KW - CyberGIS
KW - Exploratory spatial data analysis
KW - Flow mapping
KW - Flumapper
KW - Kernel density estimation
UR - http://www.scopus.com/inward/record.url?scp=84882364339&partnerID=8YFLogxK
U2 - 10.1145/2484762.2484821
DO - 10.1145/2484762.2484821
M3 - Conference contribution
AN - SCOPUS:84882364339
SN - 9781450321709
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the XSEDE 2013 Conference
Y2 - 22 July 2013 through 25 July 2013
ER -