Basic Patterns of Dream Content

Using new digital tools to explore the nature and meaning of dreaming.

Posted Sep 04, 2020

Kelly Bulkeley
Source: Kelly Bulkeley

The basic patterns of dream content are coming into sharper focus, thanks to new technologies of digital analysis. By using these tools to study large and diverse collections of high-quality dream data, and then making those tools and data publicly available, we can illuminate recurrent frequencies of dream content that others can easily review, replicate, and verify for themselves. The more we know about these basic patterns, the more we can gain helpful insights from people’s dreams regarding their mental and physical health, social relations, cultural interests, and even spiritual beliefs.

When I began this line of research in the mid-2000’s, I used the resources of the, a site managed by G. William Domhoff and Adam Schneider. In a paper from 2009, “Seeking patterns in dream content: A systematic approach to word searches,” drawing on the resources of the Dreambank, I included this passage in the conclusion:

“Until researchers have gathered many more high-quality reports from a wide variety of people (ideally accompanied by multiple sources of biographical data), we cannot make any definitive declarations about the universal features of human dreaming. But the results of this study suggest several testable hypotheses:

1. Dreaming perception is primarily visual, with less hearing and touch and almost no smell or taste.

2. All emotions are represented in dreams, with fear the most frequent.

3. Many types of cognitive activity occur in dreaming, especially those associated with awareness and social intelligence.

4. Aggression is more frequent than sexuality, and both are more frequent for men than for women."

Today, these same hypotheses can easily be tested with the resources of the Sleep and Dream Database (SDDb). The simplest method is to use the SDDb’s built-in word search template of keywords. The word search function has a template of 40 categories of dream content, including categories for specific types of perception, emotion, cognitive activity, and social interaction. Starting on the “Advanced Search” page, I would define the data set for this purpose by setting a word limit of 25 words, and then select a category from the keywords menu. Looking at perceptions first, the following results can be generated in a few moments:

Out of a total of 20,510 dream reports of at least 25 words in length, reported by a total of 7,335 people, a word relating to visual perception appeared at least once in 34.6% of the reports. For hearing, the figure was 10.7%, for touch, 13%, and smell and taste combined only 2.7%. Eleven years later, I would still stand by that first hypothesis.

Turning to emotions, the results of the same simple search process (define the data set as having a minimum of 25 words, and selecting a category from the keywords menu) are just as predicted. A word relating to fear appears at least once in 18.2% of the dreams. Anger appears in 7.1%, sadness in 3.7%, happiness 6.5%, and wonder/confusion 14.4%. This hypothesis seems pretty solid, too.

Cognition in dreaming is harder to study for various reasons, but the word search method can still offer some interesting results. A word relating to thinking appears at least once in 41.9% of the dreams. Some kind of speech or verbal communication appears in 37.6%, and a reference to reading or writing in 7.6%. These findings support the basic idea that dreaming has a fair amount of cognitive activity, with plenty of social communication, though more detailed studies are needed to tease out the variations between dreaming and waking cognition. The third hypothesis is worth keeping.

Social interactions in dreaming are also difficult to study, so the results here should be regarded with extra caution. Indeed, the hypothesis from 2009 may not bear contemporary scrutiny, particularly around gender differences. (When defining the data set, gender can be selected as a search variable from the constraints menu.) The SDDb word search approach yields a finding of at least one reference to physical aggression in 20.8% of the male dreams and 17.2% of the female dreams. That’s a difference, but not a huge one. With the category of sexuality, the male dreams had at least one reference in 5.8% of the reports, versus 6.6% for the female dreams. This is the reverse of the predicted difference. The results of this quick analysis confirm that overall references to physical aggression occur much more frequently than references to sexuality, but the results do not support the 2009 hypothesis about higher frequencies of both kinds of content in men’s dreams.

There are other ways to study these questions with the tools of the SDDb. For example, the “baselines” function provides the frequencies on all 40 categories for a specially curated subset of 2,094 male dreams and 3,227 female dreams. These baseline frequencies provide a kind of measuring stick for dream researchers—a more precise way of determining the average frequencies of particular types of dream content and comparing them to other sets of dreams, which might have content features that vary from the baseline patterns in interesting ways. That shall be a topic for another post.