Digital technologies have given us new ways to socialize and to track, measure, and reflect upon our socializing. Humans have always been social animals, as Aristotle said long ago, but now we’re social animals with smart phones, email, Facebook, Tubmlr, and Twitter. It’s not just that these tools and platforms dramatically expand the range of our social interactions—they do—but more importantly they enable us to observe those interactions over time in finely grained detail and analyze them for personal insight.
An unusual but promising development in this area is the use of social network analysis in the study of dreams. Despite their occasionally strange and otherworldly content, people’s dreams offer a surprisingly accurate source of information about their most important emotional concerns in waking life, including their relationships with other people.
Richard Schweickert, a professor of psychology at Purdue University, has done pioneering work in demonstrating the validity of applying the latest tools of social network analysis to dream content. Schweickert (with the help of G. William Domhoff) analyzed the lengthy dream journals of three participants, 2 women and a man. He identified all the characters that appeared in the dreams and created maps of “affiliation networks” to indicate how often the various characters appeared in the same dreams together.
His results showed that all three dream series had a nonrandom “small world structure,” meaning that certain characters appeared together in the dreams far more frequently than would be predicted by chance alone.
Schweickert’s research is more than another piece of evidence supporting the notion that dreams are meaningfully structured psychological phenomena, not just random neural nonsense from the sleep-addled brain. His findings cast new light on the profoundly social nature of human dreaming, showing that dreams can be a potentially valuable mirror revealing the people who matter to us the most.
For example, the participant known as “Merri” dreamed more often of her recently deceased sister than of any living person in her current waking life. This suggests that we dream about people who are especially meaningful, not necessarily the people with whom we spend the most time.
Schweickert also noticed that another of the participants had many dreams of family members and of work colleagues, but rarely dreams including people from both those spheres of his life. This participant was an insect taxonomist by profession, prompting Schweickert to speculate that “perhaps his cognitive style is to focus”; this might account for the mutually exclusive categories of social interaction in his dreams.
What’s most exciting about these findings is that they open the door to deeper and more sophisticated examinations of our social networks. Who are the interlinked communities of people we dream about the most often? Which of our dream characters serve as mediators connecting different communities? What happens when characters we personally know appear in the same dreams as celebrities we’ve never actually met (e.g., actors, musicians, athletes)? Who are the “lone wolves” of our dream life, people who only appear by themselves and never with other characters? How do the social networks of dreaming relate to other aspects of dream content such as emotions, colors, and settings? Do we only dream of some people in happy situations, and other people only in frightening scenarios?
The technology needed to answer these questions is emerging rapidly. Better than counting Facebook friends or Twitter followers, the big data of dreaming offers a valuable source of honest, accurate insight into the intricate web of social relationships that shape our lives.
Note: this post also appears on the Huffington Post, as of September 3, 2013.