Abstract
The continuity hypothesis of dreams suggests that the content of dreams is continuous with the dreamer's waking experiences. Given the unprecedented nature of the experiences during COVID-19, we studied the continuity hypothesis in the context of the pandemic. We implemented a deep-learning algorithm that can extract mentions of medical conditions from text and applied it to two datasets collected during the pandemic: 2,888 dream reports (dreaming life experiences), and 57M tweets mentioning the pandemic (waking life experiences). The health expressions common to both sets were typical COVID-19 symptoms (e.g., cough, fever, and anxiety), suggesting that dreams reflected people's real-world experiences. The health expressions that distinguished the two sets reflected differences in thought processes: expressions in waking life reflected a linear and logical thought process and, as such, described realistic symptoms or related disorders (e.g., nasal pain, SARS, H1N1); those in dreaming life reflected a thought process closer to the visual and emotional spheres and, as such, described either conditions unrelated to the virus (e.g., maggots, deformities, snakebites), or conditions of surreal nature (e.g., teeth falling out, body crumbling into sand). Our results confirm that dream reports represent an understudied yet valuable source of people's health experiences in the real world.
Abstract (translated)
URL
https://arxiv.org/abs/2202.01176
