The Complexity Matching hypothesis for human communication
The study of human communication incorporates disciplines across the sciences and the humanities. One question that is important for better understanding and explaining human communication is how information is transmitted from one person to another person during an interaction. To communicate, humans produce and perceive complex behaviors such as vocalizations and body movements. Although researchers are beginning to better understand the production and perception of communicative behaviors, less work has focused on investigating the functions of these behaviors for information transmission during an interaction. Here, in collaboration with various co-authors, I present a hypothesis for human communication that has specific predictions for information transmission across individuals during an interaction.
The Complexity Matching hypothesis for human communication suggests that when the complex, hierarchical patterns of communicative behavior between individuals match, information transmission is enhanced. This hypothesis is motivated by work in statistical mechanics showing that when complex properties of two networks match, information transmission across the networks is optimal. In this dissertation, I present three projects that seek to test the Complexity Matching hypothesis for human communication.
First, I present initial observations of the production and convergence of hierarchical patterns of vocalizations during conversation. This study provides initial support for the Complexity Matching hypothesis and provides insights into the hierarchical properties of communicative behavior.
Next, I test the key prediction of the Complexity Matching hypothesis for human communication: enhanced information transmission. Pairs of adults were given a dyadic problem-solving task of building a tower structure out of a limited amount of materials. We observed that dyads built taller tower structures when their hierarchical patterns of vocalizations and body movements matched. These results provide initial support for the information transmission prediction of the Complexity Matching hypothesis.
Finally, I investigate the development of hierarchical structure in human communication. This study follows daylong vocal recordings of infants and their caregivers across the first two years of life. We observed evidence for hierarchical patterns of vocalizations at the earliest recordings session (second week of life) and a dynamic trajectory of complexity matching and other vocal coordination patterns across development.
This dissertation, The Complexity Matching Hypothesis for Human Communication, is submitted by Drew H. Abney in 2016 in partial fulfillment of the degree Doctor of Philosophy in Cognitive and Information Sciences at the University of California, Merced, under the guidance of dissertation committee chair Christopher T. Kello.