Power law distribution of frequencies of characters in dreams explained by random walk on semantic network

  • Richard Schweickert (Author)
  • Zhuangzhuang Xi (Author)
  • Charles Viau-Quesnel (Author)
  • Xiaofang Zheng (Author)

Identifiers (Article)

Abstract

In an individual’s dreams some characters occur more frequently than others.  In dream series of five individuals, character frequencies follow a power law probability distribution, a distribution often found for contact with people in waking life.  Knowing the form of the distribution is important for statistical considerations, because a power law distribution is highly skewed.  The form also constrains explanations of how characters are generated in dreams.  Character generation is analogous to naming people in a verbal fluency task.  We explain the power law with an established model for this task, a random walk on an individual’s semantic memory for people and their associations.  We demonstrate with simulations that a random walk on such a network can produce a power law character frequency distribution, whether the random walk is self-avoiding or not and whether the network is connected or not.   

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Published
2020-09-28
Language
en
Keywords
Zipf's Law; Dream characters; Social network
How to Cite
Schweickert, R., Xi, Z., Viau-Quesnel , C., & Zheng, X. (2020). Power law distribution of frequencies of characters in dreams explained by random walk on semantic network. International Journal of Dream Research, 13(2), 192-201. https://doi.org/10.11588/ijodr.2020.2.71370