Multi-network Analysis of Kindergarten Children's Interactions as a Foundation for Drosophila melanogaster Interaction Networks
Year: 2017
Type: dissertation
Abstract: Group structure is important for social animals like humans, where who we interact with can influence both our happiness, and our health. One of the ways we can examine a group’s organizational structure is through social network analysis. Traditionally, networks have only been extracted and examined for a single type of interaction between individuals (e.g. friendship, smoking, happiness). Yet we know that most animals, including humans, interact in multiple ways, and these different interactions and their targets may be related. Here, I take an unbiased multi-network approach to adapt existing methods into a protocol to investigate relationships between interaction types and their contributions to group structure. Application of this method to a dataset of kindergarten children’s interactions reveals non-trivial underlying patterns in children’s classroom social structures. Potential applications of this protocol to other social groups, particularly Drosophila, are discussed.
Source: TSpace (University of Toronto)
Author: Mireille Golemiec
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2801035271