Unraveling the Web of Personality Judgments: The Influence of Social Networks on Personality Assessment


  • The characters depicted in this manuscript are purely fictitious and any resemblance to persons (especially authors) living, dead, or included in this special issue is purely coincidental. This research was supported, in part, by ADAMHA National Research Award MH14257 while the first author was a postdoctoral trainee in the Quantitative Methods Program of the Department of Psychology. University of Illinois, Urbana-Champaign. The second author wished to acknowledge the support provided to him by the University of Illinois University Scholars Program. Helpful suggestions from Steve West, David Funder, Jim Ennis, and an anonymous reviewer are very gratefully acknowledged.

Address correspondence to Alaina Kanfer, National Center for Super-computing Operations, 605 E. Springfield, Champaign, IL 61820. Sadly, Jeffrey S. Tanaka died November 3, 1992. His death is a great loss, professional and personal, to many.


ABSTRACT Contemporary assessment models have focused on the degree to which self- and other reports of personality description agree in an effort to define consensus and agreement about personality attributes. In general, we believe that analyses of this type of data have been limited in that they tend to focus on both simple models (usually dyad-based) and simple aggregations of data (usually correlations between self- and other ratings). In addition, the behaviors used as stimuli in experimental settings lack the richness of behaviors in natural social settings. Here, we present some ideas from social network models in an effort to influence broader conceptualizations of agreement and consensus in assessment. Social network models provide a more complete description of interpersonal behavior beyond the dyadic level in both laboratory and natural settings. After defining some basic social network concepts, we go on to suggest the applicability of these concepts to personality assessment and, more specifically, to how these models might be used to study self-other agreement and consensus about personality judgments. Empirical data are used to illustrate social network concepts in the domain of personality assessment.