The organization of semantic associations between senses in language

We took advantage of the semantic proximity captured by Word Embeddings to identify semantic associations between senses, as embedded in language. We explored the structure of the network of semantic associations between senses arising from English word vectors of different sense modalities that are especially closer to each other. Our results lead to semantic domains where closer associations between the senses emerge. Such domains are related to functional and physico-chemical dimensions and exhibit affective differences. Our research shows that language reflects on an abstract level, the organization of associations between the senses, and therefore, it is an effective means to study them. Furthermore, our crossmodal semantic association network provides a novel approach to study the associations between the senses which has implications both for research and practice.