Conveying (discrete) emotionality with novel words

Affective dimensions (i.e., valence and arousal) and discrete basic emotions (i.e., anger, disgust, fear, happiness, sadness) are the main affective sources of information that explain the semantic features of words. Recent studies suggest that humans are able to assign emotionality even to pseudowords, plausible verbal stimuli that do not belong to a given language which serve as proxies for never encountered, real words (i.e., novel words). So far, evidence at our disposal is mainly limited to valence (i.e., the hedonic tone of a words’ reference, from pleasant to unpleasant), while investigating discrete emotionality is required for a more refined understanding of the processes at hand. Here, across three experiments, we probed i) humans’ ability to convey discrete emotions when generating novel word stimuli to express the meanings of given emotional words, and ii) humans’ ability to decode or understand such emotionality when processing these human-generated novel words. Leveraging estimates from a word embedding model, results showed that individuals can reliably encode and decode novel conceptual information carrying emotional information, with a better performance for anger and happiness stimuli. Theoretically, these processes can be interpreted from an evolutionary perspective and, more broadly, they can be traced back to humans’ ability to process systematic, non-arbitrary form-meaning information.