Tanaka, K., & Vega Yon, G. G. (2022) Imaginary network motifs: Structural patterns of false positives and negatives in social networks.

Abstract: We advance a theory of Cognitive Social Structures to systematically investigate structural patterns of false positives and negatives that people make when they perceive their social network. Prior studies have shown that people encode, store and recall social information using relational schemas called network motifs, such as reciprocity and triadic closure. However, existing literature did not differentiate various patterns that occur as people overestimate or underestimate the existence of ties on network motifs. Here, we propose a theoretical framework to categorize three classes of imaginary network motifs as combinations of accurately and erroneously perceived ties: (a) partially false, (b) completely false, and (c) mixed false. Then, 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 in mind. The findings advance our understanding of perception gaps between actual and perceived networks and have implications for designing more accurate network modeling and sampling.