  In this paper, we argue that some fundamental concepts and tools of signal
processing may be effectively applied to represent and interpret social
cognition processes. From this viewpoint, individuals or, more generally,
social stimuli are thought of as a weighted sum of harmonics with different
frequencies: Low frequencies represent general categories such as gender,
ethnic group, nationality, etc., whereas high frequencies account for personal
characteristics. Individuals are then seen by observers as the output of a
filter that emphasizes a certain range of high or low frequencies. The
selection of the filter depends on the social distance between the observing
individual or group and the person being observed as well as on motivation,
cognitive resources and cultural background. Enhancing low- or high-frequency
harmonics is not on equal footing, the latter requiring supplementary energy.
This mirrors a well-known property of signal processing filters. More
generally, in the light of this correspondence, we show that several
established results of social cognition admit a natural interpretation and
integration in the signal processing language. While the potential of this
connection between an area of social psychology and one of information
engineering appears considerable (compression, information retrieval,
filtering, feedback, feedforward, sampling, aliasing, etc.), in this paper we
shall limit ourselves to laying down what we consider the pillars of this
bridge on which future research may be founded.
