Detecting associations between dietary supplement intake and sentiments within mental disorder tweets
Detecting associations between dietary supplement intake and sentiments within mental disorder tweets
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DOI：
10.1177/1460458219867231
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发表时间：
2019-09-30
影响因子：
3
通讯作者：
Zhang, Rui
中科院分区：
文献类型：
--
作者：
Wang, Yefeng;Zhao, Yunpeng;Zhang, Rui
许多精神障碍患者服用膳食补充剂，但他们的使用模式尚不清楚。在这项研究中，我们开发了一种方法，在Twitter数据中检测膳食补充剂摄入量和精神障碍之间的关联信号。我们开发了一个带标注的数据集，并训练了卷积神经网络分类器，该分类器可以识别膳食补充剂摄入的语言使用模式，F1得分为0.899，准确率为0.900，召回率为0.900。使用分类器，我们发现褪黑激素和维生素D是自我诊断精神障碍的推特用户最常用的补充剂。使用语言调查和字数统计进行的情绪分析表明，在发布精神障碍自我诊断的推特用户中，表明补充摄入的用户比那些没有提到补充摄入的用户更活跃，表达更多的负面情绪和更少的积极情绪。
Many patients with mental disorders take dietary supplement, but their use patterns remain unclear. In this study, we developed a method to detect signals of associations between dietary supplement intake and mental disorder in Twitter data. We developed an annotated dataset and trained a convolutional neural network classifier that can identify language use pattern of dietary supplement intake with an F1-score of 0.899, a precision of 0.900, and a recall of 0.900. Using the classifier, we discovered that melatonin and vitamin D were the most commonly used supplements among Twitter users who self-diagnosed mental disorders. Sentiment analysis using Linguistic Inquiry and Word Count has shown that among Twitter users who posted mental disorder self-diagnosis, users who indicated supplement intake are more active and express more negative emotions and fewer positive emotions than those who have not mentioned supplement intake.