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A Timeline Extraction Approach to Derive Drug Usage Patterns in Pregnant Women Using Social Media


Abstract Proliferation of social media websites and discussion forums in the last decade has resulted in social media mining emerging as an effective mechanism to extract consumer patterns. Most research on social media and pharmacovigilance have concentrated on

Adverse Drug Reaction (ADR) identification. Such methods employ a step of drug search followed by classification of the associated text as consisting an ADR or not. Although this method works efficiently for ADR classifications, if ADR evidence is present in users posts over time, drug mentions fail to capture such ADRs. It also fails to record additional user information which may provide an opportunity to perform an in-depth analysis for lifestyle habits and possible reasons for any medic... (more)
Created Date 2016
Contributor Chandrashekar, Pramod Bharadwaj Chandrashekar (Author) / Davulcu, Hasan (Advisor) / Gonzalez, Graciela (Advisor) / Hsiao, Sharon (Committee member) / Arizona State University (Publisher)
Subject Computer science / Biostatistics / Biomedical Informatics / Classification / Natural Language Processing / Pharmacovigilance / Pregnancy / Social Media
Type Masters Thesis
Extent 52 pages
Language English
Rights All Rights Reserved
Note Masters Thesis Computer Science 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis