Imaginary network motifs: Structural patterns of false positives and negatives in social networks

TY - JOUR

T1 - Imaginary network motifs:

T2 - Structural patterns of false positives and negatives in social networks

AU - Tanaka, Kyosuke

AU - Vega Yon, George

PY - 2024/7

Y1 - 2024/7

N2 - We examine the structural patterns in the cognitive representation of social networks by systematically classifying false positives and negatives. Although existing literature on Cognitive Social Structures (CSS) has begun exploring false positives and negatives by comparing actual and perceived networks, it has not differentiated simultaneous occurrences of true and false positives and negatives on network motifs, such as reciprocity and triadic closure. Here, we propose a theoretical framework to categorize three classes of errors we call imaginary network motifs as combinations of accurately and erroneously perceived ties: (a) partially false, (b) completely false, and (c) mixed false. Using four published CSS data sets, we empirically test which imaginary network motifs are significantly more or less present in different types of perceived networks than the corresponding actual networks. Our results confirm that people not only fill in the blanks as suggested in the prior research but also conceive other imaginary structures. The findings advance our understanding of perception gaps between actual and perceived networks and have implications for designing more accurate network modeling and sampling.

AB - We examine the structural patterns in the cognitive representation of social networks by systematically classifying false positives and negatives. Although existing literature on Cognitive Social Structures (CSS) has begun exploring false positives and negatives by comparing actual and perceived networks, it has not differentiated simultaneous occurrences of true and false positives and negatives on network motifs, such as reciprocity and triadic closure. Here, we propose a theoretical framework to categorize three classes of errors we call imaginary network motifs as combinations of accurately and erroneously perceived ties: (a) partially false, (b) completely false, and (c) mixed false. Using four published CSS data sets, we empirically test which imaginary network motifs are significantly more or less present in different types of perceived networks than the corresponding actual networks. Our results confirm that people not only fill in the blanks as suggested in the prior research but also conceive other imaginary structures. The findings advance our understanding of perception gaps between actual and perceived networks and have implications for designing more accurate network modeling and sampling.

KW - Social Networks

KW - Network Perceptions

KW - Cognitive Social Structures

KW - Network Motifs

KW - Cognitive Errors

KW - Cognitive errors

KW - Network perceptions

KW - Social networks

KW - Network motifs

UR - http://www.scopus.com/inward/record.url?scp=85179162089&partnerID=8YFLogxK

U2 - 10.1016/j.socnet.2023.11.005

DO - 10.1016/j.socnet.2023.11.005

M3 - Journal article

SN - 0378-8733

VL - 78

SP - 65

EP - 80

JO - Social Networks

JF - Social Networks

ER -