Differential Association Theory, Social Learning Theory, and Technocrime

Abstract

This chapter offers thoughts on necessary future directions of theoretical studies on cybercrime generally, and differential association theory (DAT) and social learning theory (SLT) specifically. In the case of cybercrime, DAT proposes that interaction with differential associates who engage in technocrime will increase not only the actors' knowledge on how to engage in technocrime, but also aids in the acquisition of the motives and drives needed for participating in this illegal activity. SLT proposes that interaction with differential associates who engage in technocrime will cause a person to form definitions favorable or unfavorable to technocrime through an operant-conditioning-based learning process. The social learning process then repeats itself, which can either perpetuate cybercrime or abstinence from cybercrime, while also allowing for people to engage in cybercrime sporadically. Recently, scholars have discussed the roles played by associates in the causation of crime, a conversation that is especially relevant to the online world in which cybercrime occurs.