ArticleRoyal Society open science2020
Our dreams, our selves: automatic analysis of dream reports.
Article in Royal Society open science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 32 citations in OpenAlex.
- Dream Experiences During Intensive Care Unit Stay: Occurrence, Content, Vividness and Associated Factors.Nursing in critical care · 2025Article
- Dreams are more "predictable" than you think.Frontiers in sleep · 2025Article
- Dream content influences daily spirituality.Frontiers in psychology · 2025Article
- New strategies for the cognitive science of dreaming.Trends in cognitive sciences · 2024Review
- The influence of intentions on dream content.Sleep advances : a journal of the Sleep Research Society · 2024Article
- Epidemic dreams: dreaming about health during the COVID-19 pandemic.Royal Society open science · 2022Article
- The Language of Dreams: Application of Linguistics-Based Approaches for the Automated Analysis of Dream Experiences.Clocks & sleep · 2021Review
- Dreaming during lockdown: a quali-quantitative analysis of the Italian population dreams during the first COVID-19 pandemic wave.Research in psychotherapy (Milano) · 2021Article
- Our dreams, our selves: automatic analysis of dream reports.Royal Society open science · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sleep scientists have shown that dreaming helps people improve their waking lives, and they have done so by developing sophisticated content analysis scales. Dream analysis entails time-consuming manual annotation of text. That is why dream reports have been recently mined with algorithms, and these algorithms focused on identifying emotions. In so doing, researchers have not tackled two main technical challenges though: (i) how to mine aspects of dream reports that research has found important, such as characters and interactions; and (ii) how to do so in a principled way grounded in the literature. To tackle these challenges, we designed a tool that automatically scores dream reports by operationalizing the widely used dream analysis scale by Hall and Van de Castle. We validated the tool's effectiveness on hand-annotated dream reports (the average error is 0.24), scored 24 000 reports-far more than any previous study-and tested what sleep scientists call the 'continuity hypothesis' at this unprecedented scale: we found supporting evidence that dreams are a continuation of what happens in everyday life. Our results suggest that it is possible to quantify important aspects of dreams, making it possible to build technologies that bridge the current gap between real life and dreaming.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.