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Dream content discovery from social media using natural language processing

Anubhab Das, Sanja Šćepanović, Luca Maria Aiello, Remington Mallett, Deirdre Barrett, Daniele Quercia

EPJ Data Science May 23, 2025 DOI: 10.1140/epjds/s13688-025-00554-w (opens in new tab)

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Study at a glance

AI-extracted from the abstract
Characteristics Data-driven mixed-method analysis Peer reviewed
Sample size 44,213
Population Dream reports from Reddit's r/Dreams subreddit
Topics Dreaming
Keywords Dream Content measure theory Social media Natural archaeology Artificial intelligence Natural language processing World wide web
Key points Natural language processing of 44,213 dream reports identified 217 topics grouped into 22 larger themes, revealing unique patterns in nightmare and recurring dreams, a greater predominance of indoor settings than previously stipulated, and changes in collective dream content around major events like the COVID-19 pandemic and the Russo-Ukrainian war.

Abstract

Dreaming is a fundamental but not fully understood part of human experience. Traditional dream content analysis practices, while popular and aided by over 130 unique scales and rating systems, have limitations. Often based on retrospective surveys or lab studies, and sometimes on in-home dream reports collected over some days, they struggle to be applied on a large scale or to show the importance and connections between different dream themes. To overcome these issues, we conducted data-driven mixed-method analysis identifying topics in free-form dream reports through natural language processing. We applied this analysis on 44,213 dream reports from Reddit’s r/Dreams subreddit, where we uncovered 217 topics, grouped into 22 larger themes: the most extensive collection of dream topics to date. We validated our topics by comparing it to the widely-used Hall and van de Castle scale. Going beyond traditional scales, our method can find unique patterns in different dream types (like nightmares or recurring dreams), understand topic importance and connections (like finding a greater predominance of indoor location settings in Reddit dreams than what was in general stipulated by previous work), and observe changes in collective dream experiences over time and around major events (like the COVID-19 pandemic and the recent Russo-Ukrainian war). We envision that the applications of our method will provide valuable insights into the complex nature of dreaming and its interplay with our waking experiences.

Comparable studies

Other qualitative studies on dreaming, most cited first.

Study Year Design Participants
The Other as a Nightmare: The Israeli-Arab Encounter as Reflected in Children's Dreams in Israel and the West Bank Jewish and Arab fifth to seventh graders living in various settings in Israel and the... 1989 Qualitative content analysis n = 212
Nonwaking Responses to Waking Stressors: Dreams and Nightmares1 Men from the cohort eligible for military duty during the Vietnam Conflict, varying in... 1990 Survey interview study n = 442
Communing with the Gods: The Dreaming Brain in Cross-cultural Perspective 2011 Phenomenological study
Partial memory reinstatement while (lucid) dreaming to change the dream environment. Lucid dreamers 2020 Qualitative study
Strange themes in pandemic dreams: Insomnia was associated with more negative, anxious and death‐related dreams during the COVID‐19 pandemic Global survey participants 2022 Longitudinal mixed-methods study n = 2,240

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