Author/Authors :
LIU, Jingfang Dept. of Information Management - School of Management - Shanghai University, China , JIANG, Xiaoyan Dept. of Information Management - School of Management - Shanghai University, China , CHEN, Qiangyuan Dept. of Economics - School of Economics - Shanghai University, China , SONG, Mei Dept. of Software Engineering - School of Smart Education - Jiangsu Normal University, China , LI, Jia Dept. of Management Science and Engineering - School of Business - East China University of Science and Technology, China
Abstract :
Background: The posts related to Adverse Drug Reaction (ADR) on social websites are believed to be valuable
resource for post-marketing drug surveillance. Beyond domain feature, the aim of this study was to find a
more effective method to detect ADR related post.
Methods: We conducted experiment on posts using sentiment features from March 8 to May 20 in 2016 in
Shanghai of China. Firstly, the diabetes posts were collected; the 1814 posts were annotated by hand. Secondly,
sentiment features set were generated and the
2
(CHI) statistics were used to select feature. Finally, we evaluated
the effectiveness of our method using the different feature sets.
Results: By comparing the posts detection performance of different feature sets, using sentiment features by
CHI statistics can improve ADR related post detection performance. By comparing the ADR-related group
with the non-ADR group, performance of ADR related post detection was better than the performance of non-
ADR post detection. We could obtain highest performance owing to introducing sentiment feature and using
CHI feature selection technique, and the method was proved to be effective during detecting post related to
ADR.
Conclusion: By using sentiment feature and CHI feature selection technique, we can get an effective method
to detect post related to ADR.
