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Iranian Journal of Public Health، جلد ۴۷، شماره ۶، صفحات ۸۶۱-۸۶۷
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Adverse Drug Reaction Related Post Detecting Using Sentiment Feature
چکیده انگلیسی مقاله 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 (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.
کلیدواژه‌های انگلیسی مقاله Adverse drug reaction, Post, Sentiment feature
نویسندگان مقاله | Jingfang LIU
Dept. of Information Management, School of Management, Shanghai University, Shanghai 200444, China


| Xiaoyan JIANG
Dept. of Economics, School of Economics, Shanghai University, Shanghai 200444, China


| Qiangyuan CHEN
Dept. of Software Engineering, School of Smart Education, Jiangsu Normal University, Xuzhou 221116, China


| Mei SONG
Dept. of Management Science and Engineering, School of Business, East China University of Science and Technology, Shanghai 200237, China


| Jia LI


نشانی اینترنتی http://ijph.tums.ac.ir/index.php/ijph/article/view/13762
فایل مقاله اشکال در دسترسی به فایل - ./files/site1/rds_journals/86/article-86-658890.pdf
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Original Article(s)
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