Core features: measures and characterization for different languages

Abstract

According to the feature-based view of semantic representation, concepts can be represented as distributed networks of semantic features, which contribute with different weights to determine the overall meaning of a concept. The study of semantic features, typically collected in property generation tasks, is enriched with measures indicating the informativeness and distinctiveness of a given feature for the related concepts. However, while these measures have been provided in several languages (e.g. Italian, Spanish and English), they have hardly been applied comparatively across languages. The purpose of this paper is to investigate language-related differences and similarities emerging from the semantic representation of aggregated core features. Features with higher salience for a set of concrete concepts are identified and described in terms of their feature type. Then, comparisons are made between domains (natural vs. artefacts) and languages (Italian, Spanish and English) and descriptive statistics are provided. These results show that the characterization of concrete concepts is overall fairly stable across languages, although interesting cross-linguistic differences emerged. We will discuss the implications of our findings in relation to the theoretical paradigm of semantic feature norms, as well as in relation to speakers mutual understanding in multilingual settings.