Exploring the interplay of individual traits and interaction dynamics in preschool social networks
G\"ul\c{s}ah Ak\c{c}ak{\i}r, Amina Azaiez, Alberto Ceria, Clara, Eminente, Guglielmo Ferranti, Govind Gandhi, Aishvarya Raj, Iacopo Iacopini

TL;DR
This study analyzes preschool children's face-to-face interactions over a year, linking individual traits like age, sex, language skills, and siblings to their social contact patterns and group dynamics.
Contribution
It introduces a comprehensive analysis combining sensor data and metadata to reveal how individual characteristics influence early social network structures.
Findings
Children with siblings have higher network centrality.
Age and language scores significantly affect interaction patterns.
Group affinity impacts group persistence and social embedding.
Abstract
Several studies have investigated human interaction using modern tracking techniques for face-to-face encounters across various settings and age groups. However, little attention has been given to understanding how individual characteristics relate to social behavior. This is particularly important in younger age groups due to its potential effects on early childhood development. In this study, conducted during the Complexity 72h Workshop, we analyze human social interactions in a French preschool, where children's face-to-face interactions were monitored using proximity sensors over an academic year. We use metadata from parent surveys and preschool linguistic tests, covering demographic information and home habits, to examine the interplay between individual characteristics and contact patterns. Using a mixture of approaches, from random forest classifiers to network-based metrics at…
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Taxonomy
TopicsChild Development and Digital Technology
