Migraine is a high-prevalence and disabling neurological disorder. However, information migraine management in real-world settings could be limited to traditional health information sources. In this paper, we (i) verify that there is substantial migraine-related chatter available on social media (Twitter and Reddit), self-reported by migraine sufferers; (ii) develop a platform-independent text classification system for automatically detecting self-reported migraine-related posts, and (iii) conduct analyses of the self-reported posts to assess the utility of social media for studying this problem. We manually annotated 5750 Twitter posts and 302 Reddit posts. Our system achieved an F1 score of 0.90 on Twitter and 0.93 on Reddit. Analysis of information posted by our 'migraine cohort' revealed the presence of a plethora of relevant information about migraine therapies and patient sentiments associated with them. Our study forms the foundation for conducting an in-depth analysis of migraine-related information using social media data.
翻译:在本文中,我们(一) 核实在社会媒体(Twitter和Reddit)上(偏头痛患者自我报告)有大量偏头痛相关言论;(二) 开发一个自发的文本分类系统,自动检测自报的偏头痛相关职位;以及(三) 对自报职位进行分析,以评估社会媒体对研究这一问题的效用。我们用手写了5 750个Twitter文章和302个Reddit文章。我们的系统在Twitter上达到了0.90分F1分,在Reddit上达到了0.93分。分析我们的“Migraine帮”张贴的信息显示存在大量有关偏头痛疗法和患者情绪的信息。我们的研究构成了利用社会媒体数据深入分析与偏头痛有关的信息的基础。