TY - GEN
T1 - Mining internet media for monitoring changes of public emotions about infectious diseases
AU - Choi, Sungwoon
AU - Lee, Jangho
AU - Pack, Sangheon
AU - Chang, Yoon Seok
AU - Yoon, Sungroh
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT and Future Planning, MSIP) [No. 2011-0009963 and No. 2015M3A9A7029735], by the Future Flagship Program (10053249), by the Korean National Police Agency funded by MSIP (PA-C000001), by grant from the Seoul National University Bundang Hospital Research Fund (12-2013-009) and by a research grant from Samsung Advanced Institute of Technology.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/6/20
Y1 - 2016/6/20
N2 - The Internet encompasses websites, email, social media, and Internet-based television. Given the widespread use of networked computers and mobile devices, it has become possible to monitor the behavior of Internet users by examining their access logs and queries. Based on large-scale web and text mining of Internet media articles and associated user comments, we propose a framework to rapidly monitor how the emotion of the public changes over time and apply the framework to a real case of an infectious disease. The proposed methodology will be helpful for performing cost-effective and time-efficient public health monitoring that otherwise would take orders-of-magnitude more time and resources if traditional epidemiology techniques were used.
AB - The Internet encompasses websites, email, social media, and Internet-based television. Given the widespread use of networked computers and mobile devices, it has become possible to monitor the behavior of Internet users by examining their access logs and queries. Based on large-scale web and text mining of Internet media articles and associated user comments, we propose a framework to rapidly monitor how the emotion of the public changes over time and apply the framework to a real case of an infectious disease. The proposed methodology will be helpful for performing cost-effective and time-efficient public health monitoring that otherwise would take orders-of-magnitude more time and resources if traditional epidemiology techniques were used.
UR - http://www.scopus.com/inward/record.url?scp=84982795750&partnerID=8YFLogxK
U2 - 10.1109/ICDEW.2016.7495619
DO - 10.1109/ICDEW.2016.7495619
M3 - Conference contribution
AN - SCOPUS:84982795750
T3 - 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016
SP - 68
EP - 70
BT - 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016
Y2 - 16 May 2016 through 20 May 2016
ER -
