DocumentCode :
1823623
Title :
A framework for detecting public health trends with Twitter
Author :
Parker, Julian ; Yifang Wei ; Yates, Andrew ; Frieder, O. ; Goharian, Nazli
Author_Institution :
Dept. of Comput. Sci., Georgetown Univ., Washington, DC, USA
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
556
Lastpage :
563
Abstract :
Traditional public health surveillance requires regular clinical reports and considerable effort by health professionals to analyze data. Therefore, a low cost alternative is of great practical use. As a platform used by over 500 million users worldwide to publish their ideas about many topics, including health conditions, Twitter provides researchers the freshest source of public health conditions on a global scale. We propose a framework for tracking public health condition trends via Twitter. The basic idea is to use frequent term sets from highly purified health-related tweets as queries into a Wikipedia article index - treating the retrieval of medically-related articles as an indicator of a health-related condition. By observing fluctuations in frequent term sets and in turn medically-related articles over a series of time slices of tweets, we detect shifts in public health conditions and concerns over time. Compared to existing approaches, our framework provides a general a priori identification of emerging public health conditions rather than a specific illness (e.g., influenza) as is commonly done.
Keywords :
information retrieval; medical information systems; social networking (online); Twitter; Wikipedia article index; health-related condition; medically-related article retrieval; public health conditions; public health trends detection; Electronic publishing; Encyclopedias; Internet; Labeling; Public healthcare; Twitter; Wikipedia; health surveillance; item-set mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON
Type :
conf
Filename :
6785758
Link To Document :
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