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An Intelligence System based on Social Web Mining and its Application in Health Care in Hong Kong

Authors:
Kin Keung, Lai
Juan Shi
Gang Chen

Keywords: big data; Web 2.0; social web mining; opinion mining; sentiment analysis; epidemics surveillance.

Abstract:
In China, two systems—National Disease Surveillance Reporting System (NDSRS) and the National Adverse Drug Reaction (ADR) Monitoring System--have been established for monitoring infectious diseases and for reporting ADR events. However, surveys have shown that nontrivial problems have affected the performance of these information systems adversely. Specifically, the absence of reasonable work and supervision systems, namely the systemic factors constitute the majority of the reasons for underperformance of these information systems. Also, not just some leaders but also quite a few doctors do not give sufficient importance to reports of infectious cases or ADR events, which is thought to be a waste of manpower and financial resources. Nowadays social media websites have attracted wide interest from both the academia and the industry, because of its very large user base, updating in real time, abundant incoming data and the fact that it offers prolific information about consumers’ behavioral characteristics. In this proposal, we plan to address the aforementioned issues by implementing an Intelligence System based on Social Web Mining (ISSWM). ISSWM can help detect ADR events, assess the trends of infectious diseases, probe people’s opinions towards some medical institutions or on healthcare related issues in real-time, at a cost that is extremely low compared with the existing systems.

Pages: 42 to 46

Copyright: Copyright (c) IARIA, 2015

Publication date: August 23, 2015

Published in: conference

ISSN: 2308-4340

ISBN: 978-1-61208-428-2

Location: Venice, Italy

Dates: from August 23, 2015 to August 28, 2015