Kyosuke Tanake (with & Contractor, N. S) will present the paper: Knowing is now enough: How network awareness and acuity are associated at 72th Annual Conference of the International Communication Association which takes place 26-30 May in Paris, France.

As network research has shown, accurate awareness of a social network brings network advantage (e.g., informal power, fast promotion, and high task performance) to members in groups and organizations. This is because it assumes that those who accurately perceive their social network (i.e., high network awareness) can also navigate the social world with more precision, which we call network acuity. However, it is unclear whether this assumption holds true or the reverse causation exists—network acuity impacts network awareness. Here, we test this assumption using cross-lag panel modeling on longitudinal network data from a laboratory experiment where 405 participants who were organized in 23 networks engaged in five rounds of a network routing task. Additionally, we identify who is more likely to be high on network awareness and acuity, respectively. Our results show that in contrast to the existing assumption, high network acuity positively predicts network awareness instead of the other way around. They suggest that effective navigation of their social network shapes an accurate awareness of the network. We also find that women and those who are popular in the network tend to be high on both network awareness and acuity. Whereas high conscientiousness and cognitive ability are only associated with high network awareness, high self-monitoring is related to high network acuity. These findings provide new insights into how people navigate organizational networks to accomplish their tasks and goals.

He will also (with Vega Yon) present Imaginary network motifs: Structural patterns of false positives and negatives in social networks.

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.