@article{Schweickert_Xi_Viau-Quesnel_Zheng_2020, title={Power law distribution of frequencies of characters in dreams explained by random walk on semantic network}, volume={13}, url={https://journals.ub.uni-heidelberg.de/index.php/IJoDR/article/view/71370}, DOI={10.11588/ijodr.2020.2.71370}, abstractNote={<p>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.   </p>}, number={2}, journal={International Journal of Dream Research}, author={Schweickert, Richard and Xi, Zhuangzhuang and Viau-Quesnel , Charles and Zheng, Xiaofang}, year={2020}, month={Sep.}, pages={192–201} }