Sudden Unexpected Death in Epilepsy (SUDEP) remains a leading cause of death in people with epilepsy. Despite the constant risk for patients and bereavement to family members, to date the physiological mechanisms of SUDEP remain unknown. Here we explore the potential to identify putative predictive signals of SUDEP from online digital behavioral data using text and sentiment analysis. Specifically, we analyze Facebook timelines of six epilepsy patients deceased due to SUDEP, donated by surviving family members. We find preliminary evidence for behavioral changes detectable by text and sentiment analysis tools. Namely, in the months preceding their SUDEP event patient social media timelines show: i) increase in verbosity; ii) increased use of functional words; and iii) sentiment shifts as measured by different sentiment analysis tools. Combined, these results suggest that social media engagement, as well as its sentiment, may serve as possible early-warning signals for SUDEP in people with epilepsy. While the small sample of patient timelines analyzed in this study prevents generalization, our preliminary investigation demonstrates the potential of social media data as complementary data in larger studies of SUDEP and epilepsy.
翻译:精神分裂症(SUDEP)的突发意外死亡仍然是癫痫患者死亡的一个主要原因。尽管患者和家人不断面临风险和丧命,但迄今为止SUDEP的生理机制仍然未知。在这里,我们探索了利用文本和情绪分析从在线数字行为数据中确定SUDEP的推定预测信号的可能性。具体地说,我们分析了由幸存的家庭成员捐赠的由SUDEP导致的6名癫痫患者的Facebook时间表。我们发现了可以通过文字和情绪分析工具检测到的行为变化的初步证据。也就是说,在SUDEP事件耐心社交媒体时间表显示之前的几个月里,我们的初步调查表明,社会媒体数据有可能成为SUDEP和癫痫较大研究中的补充数据。