Abstract
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.
Original language | English |
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Title of host publication | 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 68-70 |
Number of pages | 3 |
ISBN (Electronic) | 9781509021086 |
DOIs | |
Publication status | Published - 2016 Jun 20 |
Event | 32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016 - Helsinki, Finland Duration: 2016 May 16 → 2016 May 20 |
Other
Other | 32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016 |
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Country | Finland |
City | Helsinki |
Period | 16/5/16 → 16/5/20 |
ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems
- Computational Theory and Mathematics
- Computer Networks and Communications
- Information Systems and Management
- Computer Graphics and Computer-Aided Design