Dyadic Attribution Model

Language as a symbolic medium plays an important role in virtual communications. In a primarily linguistic environment such as cyberspace, words are an expressed form of intent and actions. This paper intends to investigate the functions of words and actions in identifying behavioral anomalies of social actors in order to safeguard the virtual organization. Social actors are likened to “sensors” as they observe changes in a focal individual’s behavior during computer-mediated communications. Based on social psychology theories and pragmatic views of words and actions in online communications, this paper theorizes a dyadic attribution model that helps make sense of anomalous behavior in creative online experiments. This model is then tested in an experiment. Findings show that observation of the behavioral differences between words and actions, based on either external or internal causality, can offer increased ability to detect the compromised trustworthiness of observed individuals – possibly leading to early detection of insider threat potential. The dyadic attribution model developed in this socio-technical study can function to detect behavioral anomalies in cyberspace, and protect the operations of a virtual organization.