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
页码：1-5
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
