Secrets and Social Networks

By: Sarah K. Cowan

Published in: Current Opinion in Psychology 31 (2020)

Secrets are information kept from others; they are relational. They shape the intimacy of our relationships, what we know of others and what we infer about the world. Recent research has promoted two models of voluntary secret disclosure. The first highlights deliberate and strategic disclosure to garner support and to avoid judgment. The second maintains strategic action but foregrounds that disclosures are made in contexts which shape who is in one’s social network and who may be the recipient of a disclosure. Work outside of this main vein examines the mechanisms and motivations to share others’ secrets as well as the potential consequences of doing so. The final avenue of inquiry in this review considers how keeping secrets can change (or avoid changing) the size and composition of the secret-keeper’s social network and what information is shared within it. Understanding how secrets spread within and form social networks informs work from public health to criminology to organizational management.

Estimating Personal Network Size with Non-random Mixing via Latent Kernels

By: Swupnil Sahai, Timothy Jones*, Sarah K. Cowan & Tian Zheng

Published in: Aiello L., Cherifi C., Cherifi H., Lambiotte R., Lió P., Rocha L. (eds) Complex Networks and Their Applications VII. Complex Networks 2018. Studies in Computational Intelligence, vol 812. Springer.

A major problem in the study of social networks is estimating the number of people an individual knows. However, there is no general method to account for barrier effects, a major source of bias in common estimation procedures. The literature describes approaches that model barrier effects, or non-random mixing, but they suffer from unstable estimates and fail to give results that agree with specialists’ knowledge. In this paper we introduce a model that builds off existing methods, imposes more structure, requires significantly fewer parameters, and yet allows for greater interpretability. We apply our model on responses gathered from a survey we designed and show that our conclusions better match what sociologists find in practice. We expect that this approach will provide more accurate estimates of personal network sizes and hence remove a significant hurdle in sociological research.

“It could turn ugly”: Selective Disclosure of Political Views and Biased Network Perception

By: Sarah K. Cowan, and Delia Baldassarri

Published in: Social Networks 52 (2018)

This article documents individuals selectively disclosing their political attitudes and the consequences for social influence and the democratic process. Using a large, diverse sample of American adults, we find Americans keep their political attitudes secret specifically from those with whom they disagree. As such, they produce the experience of highly homogeneous social contexts, in which only liberal or conservative views are voiced, while dissent remains silent, and often times goes unacknowledged. This experience is not the result of homogeneous social contexts but the appearance of them. Pervasive selective disclosure creates a gap between the objective social network and the perceived social network in which political agreement is over-estimated. On the micro-level, the processes of social influence on the formation and modification of political attitudes that occur when people converse with those with whom they disagree are thwarted and on the macro-level, this mechanism of selective disclosure leads to the perception of a greatly polarized public opinion.