Public Street Surveillance: A Psychometric Study on the Perceived Social Risk
Faculty of Computing, Health and Science
School of Engineering
This study quantitatively measured the social risk perception of public street surveillance, using spatial representation and multidimensional scaling (MDS). It utilized the psychometric paradigm, a method that presents risk perception in a two factor representation, being dread and familiarity to risk. The investigation showed the social risk perception of public street surveillance as low dread and familiar risk. MDS underlying dimensions presented public street surveillance as a low sense of risk perception and a low perceived community exposure to risk. This demonstrated a perceived social benefit, outweighing the perceived risk.