Computing with words (CWW) explores the brain’s ability to handle and evaluate perceptions through language, i.e., by means of the linguistic representation of information and knowledge. On the other hand, standard preference structures examine decision problems through the decomposition of the preference predicate into the simpler situations of strict preference, indifference and incomparability. Hence, following the distinctive cognitive/neurological features for perceiving positive and negative stimuli in separate regions of the brain, we consider two separate and opposite poles of preference and aversion, and obtain an extended preference structure named the Preference–aversion (P–A) structure. In this way, examining the meaning of words under an ordinal scale and using CWW’s methodology, we are able to formulate the P–A model under a simple and purely linguistic approach to decision making, obtaining a solution based on the preference and non-aversion order.