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Dreaming is a fundamental but not fully understood part of human experiencethat can shed light on our thought patterns. Traditional dream analysispractices, while popular and aided by over 130 unique scales and ratingsystems, have limitations. Mostly based on retrospective surveys or labstudies, they struggle to be applied on a large scale or to show the importanceand connections between different dream themes. To overcome these issues, wedeveloped a new, data-driven mixed-method approach for identifying topics infree-form dream reports through natural language processing. We tested thismethod on 44,213 dream reports from Reddit's r/Dreams subreddit, where we found217 topics, grouped into 22 larger themes: the most extensive collection ofdream topics to date. We validated our topics by comparing it to thewidely-used Hall and van de Castle scale. Going beyond traditional scales, ourmethod can find unique patterns in different dream types (like nightmares orrecurring dreams), understand topic importance and connections, and observechanges in collective dream experiences over time and around major events, likethe COVID-19 pandemic and the recent Russo-Ukrainian war. We envision that theapplications of our method will provide valuable insights into the intricatenature of dreaming.

Dream Content Discovery from Reddit with an Unsupervised Mixed-Method Approach