Title :
Text Mining for Personal Health Information on Twitter
Author :
Sokolova, Marina ; Jafer, Yasser ; Schramm, David
Author_Institution :
Fac. of Med., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
With millions people discussing their Personal Health Information (PHI) online, there is a need for the development of tools that can extract and analyze such information. We introduce two semantic-based methods for mining PHI. One method uses WordNet as a source of health-related knowledge, another - terms of personal relations. Incorporating semantics gives a significant improvement in retrieval of text with PHI (paired t-test, P = 0.0001).
Keywords :
data mining; information retrieval; medical information systems; personal information systems; social networking (online); text analysis; Twitter; WordNet; health-related knowledge source; information analysis; information extraction; online PHI text mining; paired t-test; personal health information; personal relations; semantic-based methods; text retrieval improvement; Educational institutions; Medical services; Ontologies; Power capacitors; Semantics; Text mining; Twitter; Personal Health Information; Text Mining;
Conference_Titel :
Healthcare Informatics, Imaging and Systems Biology (HISB), 2012 IEEE Second International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-4803-4
DOI :
10.1109/HISB.2012.37
