期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：10
DOI：10.14569/IJACSA.2019.0101001
出版社：Science and Information Society (SAI)
摘要：The paper presents a computational method that mines, processes and analyzes Twitter data for detecting public sentiment of medicine. Self-reported patient data are collected over a period of three months by mining the Twitter feed, resulting in more than 10,000 tweets used in the study. Machine learning algorithms are used for an automatic classification of the public sentiment on selected drugs. Various learning models are compared in the study. This work demonstrates a practical case of utilizing social media in identifying customer opinions and building a drug effectiveness detection system. Our model has been validated on a tweet dataset with a precision of 70.7%. In addition, the study examines the correlation between patient symptoms and their choices for medication.
关键词：Twitter; social media; data mining; public health
