Positive and negative tie perceptual accuracy: Pollyanna principle vs. negative asymmetry explanations

Joshua E. Marineau, Giuseppe (Joe) Labianca

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We examine the affective content of ties and explore whether negative affective tie content is systematically advantaged or disadvantaged when recalling the social network as compared to positive affective tie content. We test this in three workgroups from two organizations and analyze differences in perceptual accuracy comparing negative and positive affective tie perception. We theorize that ego will be more accurate for others’ positive than negative ties due to generalized positivity bias, or the Pollyanna principle. We also theorize that ego will be more accurate for their own negative ties due to negative asymmetry perspective, as ego will attend more to those ties that pose a personal threat. Findings suggest that observers were more accurate overall about their own and others’ positive compared to negative affective ties. We conclude that the Pollyanna principle is an important factor in explaining perceptions in naturalistic cognitive networks. Supplementary analysis showed that negative ties were more likely to be missed and imagined and having a valenced tie toward another person influences perceptions of that persons’ network ties. Finally, we find that balanced and imbalanced triads were also important factors of relative accuracy. The study's contribution, limitations, and future research are also discussed.

Original languageEnglish
Pages (from-to)83-98
Number of pages16
JournalSocial Networks
Volume64
DOIs
StatePublished - Jan 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier B.V.

Keywords

  • Negative asymmetry
  • Negative ties
  • Network accuracy
  • Pollyanna principle
  • Positive ties
  • Social network perception

ASJC Scopus subject areas

  • Anthropology
  • Sociology and Political Science
  • General Social Sciences
  • General Psychology

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